Merge branch 'master' of http://git.agentlab.cn/HaoYizhi/IIabm
|
@ -12,9 +12,9 @@
|
||||||
"console": "integratedTerminal",
|
"console": "integratedTerminal",
|
||||||
"justMyCode": true,
|
"justMyCode": true,
|
||||||
"args": [
|
"args": [
|
||||||
"--exp", "test",
|
"--exp", "with_exp",
|
||||||
"--reset_db", "True",
|
"--reset_db", "True",
|
||||||
"--job", "1"
|
"--job", "24"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
]
|
]
|
||||||
|
|
|
@ -0,0 +1,85 @@
|
||||||
|
select distinct experiment.idx_scenario,
|
||||||
|
n_max_trial, prf_size, prf_conn, cap_limit_prob_type, cap_limit_level, diff_new_conn, remove_t, netw_prf_n,
|
||||||
|
mean_count_firm_prod, mean_count_firm, mean_count_prod,
|
||||||
|
mean_max_ts_firm_prod, mean_max_ts_firm, mean_max_ts_prod,
|
||||||
|
mean_n_remove_firm_prod, mean_n_all_prod_remove_firm, mean_end_ts
|
||||||
|
from iiabmdb.with_exp_experiment as experiment
|
||||||
|
left join
|
||||||
|
(
|
||||||
|
select
|
||||||
|
idx_scenario,
|
||||||
|
sum(count_firm_prod) / count(*) as mean_count_firm_prod, # Note to use count(*), to include NULL
|
||||||
|
sum(count_firm) / count(*) as mean_count_firm,
|
||||||
|
sum(count_prod) / count(*) as mean_count_prod,
|
||||||
|
sum(max_ts_firm_prod) / count(*) as mean_max_ts_firm_prod,
|
||||||
|
sum(max_ts_firm) / count(*) as mean_max_ts_firm,
|
||||||
|
sum(max_ts_prod) / count(*) as mean_max_ts_prod,
|
||||||
|
sum(n_remove_firm_prod) / count(*) as mean_n_remove_firm_prod,
|
||||||
|
sum(n_all_prod_remove_firm) / count(*) as mean_n_all_prod_remove_firm,
|
||||||
|
sum(end_ts) / count(*) as mean_end_ts
|
||||||
|
from (
|
||||||
|
select sample.id, idx_scenario,
|
||||||
|
count_firm_prod, count_firm, count_prod,
|
||||||
|
max_ts_firm_prod, max_ts_firm, max_ts_prod,
|
||||||
|
n_remove_firm_prod, n_all_prod_remove_firm, end_ts
|
||||||
|
from iiabmdb.with_exp_sample as sample
|
||||||
|
# 1 2 3 + 9
|
||||||
|
left join iiabmdb.with_exp_experiment as experiment
|
||||||
|
on sample.e_id = experiment.id
|
||||||
|
left join (select s_id,
|
||||||
|
count(distinct id_firm, id_product) as count_firm_prod,
|
||||||
|
count(distinct id_firm) as count_firm,
|
||||||
|
count(distinct id_product) as count_prod,
|
||||||
|
max(ts) as end_ts
|
||||||
|
from iiabmdb.with_exp_result group by s_id) as s_count
|
||||||
|
on sample.id = s_count.s_id
|
||||||
|
# 4
|
||||||
|
left join # firm prod
|
||||||
|
(select s_id, max(ts) as max_ts_firm_prod from
|
||||||
|
(select s_id, id_firm, id_product, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_firm, id_product) as ts
|
||||||
|
group by s_id) as s_max_ts_firm_prod
|
||||||
|
on sample.id = s_max_ts_firm_prod.s_id
|
||||||
|
# 5
|
||||||
|
left join # firm
|
||||||
|
(select s_id, max(ts) as max_ts_firm from
|
||||||
|
(select s_id, id_firm, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_firm) as ts
|
||||||
|
group by s_id) as s_max_ts_firm
|
||||||
|
on sample.id = s_max_ts_firm.s_id
|
||||||
|
# 6
|
||||||
|
left join # prod
|
||||||
|
(select s_id, max(ts) as max_ts_prod from
|
||||||
|
(select s_id, id_product, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_product) as ts
|
||||||
|
group by s_id) as s_max_ts_prod
|
||||||
|
on sample.id = s_max_ts_prod.s_id
|
||||||
|
# 7
|
||||||
|
left join
|
||||||
|
(select s_id, count(distinct id_firm, id_product) as n_remove_firm_prod
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "R"
|
||||||
|
group by s_id) as s_n_remove_firm_prod
|
||||||
|
on sample.id = s_n_remove_firm_prod.s_id
|
||||||
|
# 8
|
||||||
|
left join
|
||||||
|
(select s_id, count(distinct id_firm) as n_all_prod_remove_firm from
|
||||||
|
(select s_id, id_firm, count(distinct id_product) as n_remove_prod
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "R"
|
||||||
|
group by s_id, id_firm) as s_n_remove_prod
|
||||||
|
left join iiabmdb_basic_info.firm_n_prod as firm_n_prod
|
||||||
|
on s_n_remove_prod.id_firm = firm_n_prod.code
|
||||||
|
where n_remove_prod = n_prod
|
||||||
|
group by s_id) as s_n_all_prod_remove_firm
|
||||||
|
on sample.id = s_n_all_prod_remove_firm.s_id
|
||||||
|
) as secnario_count
|
||||||
|
group by idx_scenario
|
||||||
|
) as secnario_mean
|
||||||
|
on experiment.idx_scenario = secnario_mean.idx_scenario;
|
|
@ -0,0 +1,94 @@
|
||||||
|
select * from iiabmdb.with_exp_result limit 0, 20;
|
||||||
|
select count(distinct s_id) from iiabmdb.with_exp_result;
|
||||||
|
select count(*) from iiabmdb.with_exp_sample;
|
||||||
|
|
||||||
|
select distinct s_id, id_firm, id_product from iiabmdb.with_exp_result order by s_id, id_firm, id_product;
|
||||||
|
|
||||||
|
select distinct s_id, count(distinct id_firm, id_product) as count_firm_prod from iiabmdb.with_exp_result group by s_id;
|
||||||
|
|
||||||
|
select distinct s_id, count(distinct id_firm, id_product) as count_firm_prod
|
||||||
|
from iiabmdb.with_exp_result group by s_id;
|
||||||
|
|
||||||
|
select distinct s_id,
|
||||||
|
count(distinct id_firm, id_product) as count_firm_prod,
|
||||||
|
count(distinct id_firm) as count_firm,
|
||||||
|
count(distinct id_product) as count_prod
|
||||||
|
from iiabmdb.with_exp_result group by s_id;
|
||||||
|
|
||||||
|
# 控制问题需要处理,否则最后 experiment avg出来的东西不对
|
||||||
|
# 1 2 3
|
||||||
|
select
|
||||||
|
idx_scenario,
|
||||||
|
sum(count_firm_prod) / count(*) as mean_count_firm_prod, # Note to use count(*), to include NULL
|
||||||
|
sum(count_firm) / count(*) as mean_count_firm,
|
||||||
|
sum(count_prod) / count(*) as mean_count_prod
|
||||||
|
from (
|
||||||
|
select sample.id, idx_scenario, count_firm_prod, count_firm, count_prod
|
||||||
|
from iiabmdb.with_exp_sample as sample
|
||||||
|
left join iiabmdb.with_exp_experiment as experiment
|
||||||
|
on sample.e_id = experiment.id
|
||||||
|
left join (select s_id,
|
||||||
|
count(distinct id_firm, id_product) as count_firm_prod,
|
||||||
|
count(distinct id_firm) as count_firm,
|
||||||
|
count(distinct id_product) as count_prod
|
||||||
|
from iiabmdb.with_exp_result group by s_id) as s_count
|
||||||
|
on sample.id = s_count.s_id) as secnario_count
|
||||||
|
group by idx_scenario;
|
||||||
|
|
||||||
|
# 4 5 6
|
||||||
|
select sample.id, idx_scenario, max_ts_firm_prod, max_ts_firm, max_ts_prod
|
||||||
|
from iiabmdb.with_exp_sample as sample
|
||||||
|
left join iiabmdb.with_exp_experiment as experiment
|
||||||
|
on sample.e_id = experiment.id
|
||||||
|
left join # firm prod
|
||||||
|
(select s_id, max(ts) as max_ts_firm_prod from
|
||||||
|
(select s_id, id_firm, id_product, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_firm, id_product) as ts
|
||||||
|
group by s_id) as s_max_ts_firm_prod
|
||||||
|
on sample.id = s_max_ts_firm_prod.s_id
|
||||||
|
left join # firm
|
||||||
|
(select s_id, max(ts) as max_ts_firm from
|
||||||
|
(select s_id, id_firm, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_firm) as ts
|
||||||
|
group by s_id) as s_max_ts_firm
|
||||||
|
on sample.id = s_max_ts_firm.s_id
|
||||||
|
left join # prod
|
||||||
|
(select s_id, max(ts) as max_ts_prod from
|
||||||
|
(select s_id, id_product, min(ts) as ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "D"
|
||||||
|
group by s_id, id_product) as ts
|
||||||
|
group by s_id) as s_max_ts_prod
|
||||||
|
on sample.id = s_max_ts_prod.s_id;
|
||||||
|
|
||||||
|
# 7 8 9
|
||||||
|
select sample.id, idx_scenario, n_remove_firm_prod, n_all_prod_remove_firm, end_ts
|
||||||
|
from iiabmdb.with_exp_sample as sample
|
||||||
|
left join iiabmdb.with_exp_experiment as experiment
|
||||||
|
on sample.e_id = experiment.id
|
||||||
|
left join
|
||||||
|
(select s_id, count(distinct id_firm, id_product) as n_remove_firm_prod
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "R"
|
||||||
|
group by s_id) as s_n_remove_firm_prod
|
||||||
|
on sample.id = s_n_remove_firm_prod.s_id
|
||||||
|
left join
|
||||||
|
(select s_id, count(distinct id_firm) as n_all_prod_remove_firm from
|
||||||
|
(select s_id, id_firm, count(distinct id_product) as n_remove_prod
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
where `status` = "R"
|
||||||
|
group by s_id, id_firm) as s_n_remove_prod
|
||||||
|
left join iiabmdb_basic_info.firm_n_prod as firm_n_prod
|
||||||
|
on s_n_remove_prod.id_firm = firm_n_prod.code
|
||||||
|
where n_remove_prod = n_prod
|
||||||
|
group by s_id) as s_n_all_prod_remove_firm
|
||||||
|
on sample.id = s_n_all_prod_remove_firm.s_id
|
||||||
|
left join
|
||||||
|
(select s_id, max(ts) as end_ts
|
||||||
|
from iiabmdb.with_exp_result
|
||||||
|
group by s_id) as s_end_ts
|
||||||
|
on sample.id = s_end_ts.s_id;
|
|
@ -0,0 +1,12 @@
|
||||||
|
select * from
|
||||||
|
(select s_id, id_firm, id_product, min(ts) as ts from iiabmdb.without_exp_result
|
||||||
|
where `status` = 'D'
|
||||||
|
group by s_id, id_firm, id_product) as s_disrupt
|
||||||
|
where s_id in
|
||||||
|
(select s_id from
|
||||||
|
(select s_id, id_firm, id_product, min(ts) as ts from iiabmdb.without_exp_result
|
||||||
|
where `status` = 'D'
|
||||||
|
group by s_id, id_firm, id_product) as t
|
||||||
|
group by s_id
|
||||||
|
having count(*) > 1)
|
||||||
|
order by s_id;
|
|
@ -1,19 +1,15 @@
|
||||||
select count(*) from iiabmdb.without_exp_sample;
|
select e_id, n_disrupt_sample, total_n_disrupt_firm_prod_experiment, dct_lst_init_disrupt_firm_prod from iiabmdb.without_exp_experiment as experiment
|
||||||
|
inner join (
|
||||||
select distinct s_id from iiabmdb.without_exp_result where ts > 0;
|
select e_id, count(id) as n_disrupt_sample, sum(n_disrupt_firm_prod_sample) as total_n_disrupt_firm_prod_experiment from iiabmdb.without_exp_sample as sample
|
||||||
select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id order by max_ts;
|
inner join (
|
||||||
select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
|
select * from
|
||||||
inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
|
(select s_id, COUNT(DISTINCT id_firm, id_product) as n_disrupt_firm_prod_sample from iiabmdb.without_exp_result group by s_id
|
||||||
on a.id = b.s_id
|
) as count_disrupt_firm_prod_sample
|
||||||
|
where n_disrupt_firm_prod_sample > 1
|
||||||
|
) as disrupt_sample
|
||||||
|
on sample.id = disrupt_sample.s_id
|
||||||
group by e_id
|
group by e_id
|
||||||
order by count desc;
|
) as disrupt_experiment
|
||||||
|
on experiment.id = disrupt_experiment.e_id
|
||||||
select e_id, count, max_max_ts, dct_lst_init_remove_firm_prod from iiabmdb.without_exp_experiment as a
|
order by n_disrupt_sample desc, total_n_disrupt_firm_prod_experiment desc
|
||||||
inner join
|
limit 0, 95;
|
||||||
(select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
|
|
||||||
inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
|
|
||||||
on a.id = b.s_id
|
|
||||||
group by e_id) as b
|
|
||||||
on a.id = b.e_id
|
|
||||||
where count > 10
|
|
||||||
order by count desc;
|
|
|
@ -0,0 +1,44 @@
|
||||||
|
select max(ts_done) from iiabmdb.without_exp_sample;
|
||||||
|
select min(ts_done) from iiabmdb.without_exp_sample;
|
||||||
|
select count(*) from iiabmdb.without_exp_sample;
|
||||||
|
|
||||||
|
select distinct s_id from iiabmdb.without_exp_result where ts > 0;
|
||||||
|
select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id order by max_ts;
|
||||||
|
select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
|
||||||
|
inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
|
||||||
|
on a.id = b.s_id
|
||||||
|
group by e_id
|
||||||
|
order by count desc;
|
||||||
|
|
||||||
|
select e_id, count, max_max_ts, dct_lst_init_remove_firm_prod from iiabmdb.without_exp_experiment as a
|
||||||
|
inner join
|
||||||
|
(select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
|
||||||
|
inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
|
||||||
|
on a.id = b.s_id
|
||||||
|
group by e_id) as b
|
||||||
|
on a.id = b.e_id
|
||||||
|
where count > 10
|
||||||
|
order by count desc;
|
||||||
|
|
||||||
|
select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id;
|
||||||
|
select * from iiabmdb.without_exp_result order by s_id limit 0,50;
|
||||||
|
select s_id, COUNT(DISTINCT id_firm, id_product) as n_disrupt_firm_prod from iiabmdb.without_exp_result group by s_id;
|
||||||
|
select * from
|
||||||
|
(select s_id, COUNT(DISTINCT id_firm, id_product) as n_disrupt_firm_prod_sample from iiabmdb.without_exp_result group by s_id) as count_disrupt_firm_prod_sample
|
||||||
|
where n_disrupt_firm_prod_sample > 1;
|
||||||
|
|
||||||
|
select e_id, n_disrupt_sample, total_n_disrupt_firm_prod_experiment, dct_lst_init_disrupt_firm_prod from iiabmdb.without_exp_experiment as experiment
|
||||||
|
inner join (
|
||||||
|
select e_id, count(id) as n_disrupt_sample, sum(n_disrupt_firm_prod_sample) as total_n_disrupt_firm_prod_experiment from iiabmdb.without_exp_sample as sample
|
||||||
|
inner join (
|
||||||
|
select * from
|
||||||
|
(select s_id, COUNT(DISTINCT id_firm, id_product) as n_disrupt_firm_prod_sample from iiabmdb.without_exp_result group by s_id
|
||||||
|
) as count_disrupt_firm_prod_sample
|
||||||
|
where n_disrupt_firm_prod_sample > 1
|
||||||
|
) as disrupt_sample
|
||||||
|
on sample.id = disrupt_sample.s_id
|
||||||
|
group by e_id
|
||||||
|
) as disrupt_experiment
|
||||||
|
on experiment.id = disrupt_experiment.e_id
|
||||||
|
order by n_disrupt_sample desc, total_n_disrupt_firm_prod_experiment desc
|
||||||
|
limit 0, 95; # 20% of 475 experiment
|
|
@ -1,7 +1,13 @@
|
||||||
CREATE DATABASE iiabmdb_dissertation;
|
CREATE DATABASE iiabmdb20230818;
|
||||||
RENAME TABLE iiabmdb.not_test_experiment TO iiabmdb_dissertation.not_test_experiment,
|
RENAME TABLE iiabmdb.not_test_experiment TO iiabmdb20230818.not_test_experiment,
|
||||||
iiabmdb.not_test_result TO iiabmdb_dissertation.not_test_result,
|
iiabmdb.not_test_result TO iiabmdb20230818.not_test_result,
|
||||||
iiabmdb.not_test_sample TO iiabmdb_dissertation.not_test_sample,
|
iiabmdb.not_test_sample TO iiabmdb20230818.not_test_sample,
|
||||||
iiabmdb.test_experiment TO iiabmdb_dissertation.test_experiment,
|
iiabmdb.test_experiment TO iiabmdb20230818.test_experiment,
|
||||||
iiabmdb.test_result TO iiabmdb_dissertation.test_result,
|
iiabmdb.test_result TO iiabmdb20230818.test_result,
|
||||||
iiabmdb.test_sample TO iiabmdb_dissertation.test_sample;
|
iiabmdb.test_sample TO iiabmdb20230818.test_sample;
|
||||||
|
RENAME TABLE iiabmdb.with_exp_experiment TO iiabmdb20230818.with_exp_experiment,
|
||||||
|
iiabmdb.with_exp_result TO iiabmdb20230818.with_exp_result,
|
||||||
|
iiabmdb.with_exp_sample TO iiabmdb20230818.with_exp_sample,
|
||||||
|
iiabmdb.without_exp_experiment TO iiabmdb20230818.without_exp_experiment,
|
||||||
|
iiabmdb.without_exp_result TO iiabmdb20230818.without_exp_result,
|
||||||
|
iiabmdb.without_exp_sample TO iiabmdb20230818.without_exp_sample;
|
|
@ -0,0 +1,22 @@
|
||||||
|
自变量,level,系统恢复用时R1,产业-企业边累计扰乱次数R2,产业-企业边最大传导深度R3,产业-企业边断裂总数R4
|
||||||
|
采购策略P1,三供应商,2.144,2.826,1.156,0.7541
|
||||||
|
采购策略P1,双供应商,2.146,2.65,1.133,0.7615
|
||||||
|
采购策略P1,单供应商,2.261,2.519,1.121,0.7919
|
||||||
|
是否规模偏好P2,倾向,2.196,2.661,1.137,0.7657
|
||||||
|
是否规模偏好P2,不倾向,2.171,2.669,1.137,0.7726
|
||||||
|
最大尝试次数P3,高,2.141,2.652,1.13,0.739
|
||||||
|
最大尝试次数P3,中,2.124,2.652,1.127,0.7431
|
||||||
|
最大尝试次数P3,低,2.286,2.691,1.154,0.8254
|
||||||
|
是否已有连接偏好P4,倾向,2.191,2.663,1.133,0.7579
|
||||||
|
是否已有连接偏好P4,不倾向,2.177,2.668,1.141,0.7804
|
||||||
|
额外产能分布P5,均匀分布,2.316,2.681,1.158,0.8403
|
||||||
|
额外产能分布P5,正态分布,2.052,2.65,1.115,0.698
|
||||||
|
额外产能分布参数P6,高,1.914,2.624,1.098,0.6299
|
||||||
|
额外产能分布参数P6,中,2.202,2.666,1.142,0.7655
|
||||||
|
额外产能分布参数P6,低,2.436,2.705,1.171,0.9121
|
||||||
|
新供应关系构成概率P7,低,2.24,2.672,1.143,0.764
|
||||||
|
新供应关系构成概率P7,中,2.132,2.674,1.143,0.7859
|
||||||
|
新供应关系构成概率P7,高,2.179,2.649,1.124,0.7575
|
||||||
|
最大尝试时间步P8,低,1.726,2.646,1.123,0.7782
|
||||||
|
最大尝试时间步P8,中,2.186,2.682,1.144,0.7599
|
||||||
|
最大尝试时间步P8,高,2.64,2.667,1.143,0.7694
|
|
|
@ -0,0 +1,37 @@
|
||||||
|
idx_scenario,n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n,mean_count_firm_prod,mean_count_firm,mean_count_prod,mean_max_ts_firm_prod,mean_max_ts_firm,mean_max_ts_prod,mean_n_remove_firm_prod,mean_n_all_prod_remove_firm,mean_end_ts
|
||||||
|
0,7,1,1,uniform,5.0000,0.3000,3,3,2.7598,2.7598,2.1107,1.1107,1.1107,1.1107,0.6027,0.2120,1.5501
|
||||||
|
1,5,1,1,uniform,10.0000,0.5000,5,2,2.6596,2.6566,2.1535,1.1535,1.1535,1.1535,0.8261,0.2897,2.2541
|
||||||
|
2,3,1,1,uniform,15.0000,0.7000,7,1,2.5573,2.5528,2.1501,1.1501,1.1501,1.1501,0.9518,0.3141,3.1143
|
||||||
|
3,7,1,1,uniform,5.0000,0.3000,3,2,2.5783,2.5783,2.0834,1.0834,1.0834,1.0834,0.6046,0.2135,1.5524
|
||||||
|
4,5,1,1,uniform,10.0000,0.5000,5,1,2.5453,2.5423,2.1400,1.1400,1.1400,1.1400,0.8240,0.2836,2.3499
|
||||||
|
5,3,1,1,uniform,15.0000,0.7000,7,3,2.9137,2.9097,2.2402,1.2402,1.2402,1.2402,1.0712,0.3611,3.2996
|
||||||
|
6,7,1,1,normal,5.0000,0.5000,7,3,2.7848,2.7848,2.1185,1.1185,1.1185,1.1185,0.6004,0.2107,2.1802
|
||||||
|
7,5,1,1,normal,10.0000,0.7000,3,2,2.6091,2.6088,2.1046,1.1046,1.1046,1.1046,0.6552,0.2284,1.5981
|
||||||
|
8,3,1,1,normal,15.0000,0.3000,5,1,2.5823,2.5783,2.1762,1.1762,1.1762,1.1762,0.8678,0.3120,2.5343
|
||||||
|
9,7,1,0,uniform,5.0000,0.7000,5,3,2.7691,2.7691,2.1124,1.1124,1.1124,1.1124,0.6025,0.2118,1.8684
|
||||||
|
10,5,1,0,uniform,10.0000,0.3000,7,2,2.6766,2.6731,2.1655,1.1655,1.1655,1.1655,0.8362,0.2966,2.8036
|
||||||
|
11,3,1,0,uniform,15.0000,0.5000,3,1,2.5941,2.5893,2.1825,1.1825,1.1825,1.1825,1.0888,0.3741,2.0465
|
||||||
|
12,7,1,0,normal,10.0000,0.7000,3,1,2.4720,2.4718,2.0773,1.0773,1.0773,1.0773,0.6884,0.2366,1.6459
|
||||||
|
13,5,1,0,normal,15.0000,0.3000,5,3,2.8442,2.8432,2.1760,1.1760,1.1760,1.1760,0.8109,0.2829,2.2358
|
||||||
|
14,3,1,0,normal,5.0000,0.5000,7,2,2.6057,2.6057,2.0962,1.0962,1.0962,1.0962,0.6008,0.2107,2.1912
|
||||||
|
15,7,1,0,normal,10.0000,0.7000,5,3,2.7996,2.7996,2.1341,1.1341,1.1341,1.1341,0.6543,0.2293,1.9642
|
||||||
|
16,5,1,0,normal,15.0000,0.3000,7,2,2.6585,2.6575,2.1436,1.1436,1.1436,1.1436,0.7589,0.2680,2.6227
|
||||||
|
17,3,1,0,normal,5.0000,0.5000,3,1,2.4956,2.4947,2.0983,1.0983,1.0983,1.0983,0.7387,0.2604,1.7211
|
||||||
|
18,7,0,1,normal,10.0000,0.3000,7,1,2.5093,2.5072,2.1162,1.1162,1.1162,1.1162,0.6743,0.2309,2.6040
|
||||||
|
19,5,0,1,normal,15.0000,0.5000,3,3,2.8149,2.8137,2.1324,1.1324,1.1324,1.1324,0.7996,0.2737,1.7251
|
||||||
|
20,3,0,1,normal,5.0000,0.7000,5,2,2.6480,2.6480,2.0899,1.0899,1.0899,1.0899,0.6000,0.2105,1.8632
|
||||||
|
21,7,0,1,normal,10.0000,0.5000,7,1,2.4686,2.4684,2.0800,1.0800,1.0800,1.0800,0.6415,0.2192,2.3998
|
||||||
|
22,5,0,1,normal,15.0000,0.7000,3,3,2.8133,2.8120,2.1316,1.1316,1.1316,1.1316,0.7968,0.2722,1.7206
|
||||||
|
23,3,0,1,normal,5.0000,0.3000,5,2,2.6480,2.6480,2.0899,1.0899,1.0899,1.0899,0.6000,0.2105,1.8632
|
||||||
|
24,7,0,1,uniform,15.0000,0.5000,3,2,2.6798,2.6745,2.1838,1.1838,1.1838,1.1838,1.0057,0.3528,1.9152
|
||||||
|
25,5,0,1,uniform,5.0000,0.7000,5,1,2.4497,2.4491,2.0638,1.0638,1.0638,1.0638,0.6088,0.2131,1.9509
|
||||||
|
26,3,0,1,uniform,10.0000,0.3000,7,3,2.9055,2.9040,2.2318,1.2318,1.2318,1.2318,0.9118,0.3242,2.9552
|
||||||
|
27,7,0,0,normal,15.0000,0.5000,5,2,2.7160,2.7156,2.1539,1.1539,1.1539,1.1539,0.7907,0.2747,2.2006
|
||||||
|
28,5,0,0,normal,5.0000,0.7000,7,1,2.4379,2.4377,2.0512,1.0512,1.0512,1.0512,0.6013,0.2109,2.2356
|
||||||
|
29,3,0,0,normal,10.0000,0.3000,3,3,2.7853,2.7851,2.1053,1.1053,1.1053,1.1053,0.6840,0.2392,1.6286
|
||||||
|
30,7,0,0,uniform,15.0000,0.7000,7,2,2.6798,2.6756,2.1821,1.1821,1.1821,1.1821,0.9777,0.3358,3.0720
|
||||||
|
31,5,0,0,uniform,5.0000,0.3000,3,1,2.5038,2.5011,2.1131,1.1131,1.1131,1.1131,0.7916,0.2853,1.7922
|
||||||
|
32,3,0,0,uniform,10.0000,0.5000,5,3,2.9141,2.9126,2.2385,1.2385,1.2385,1.2385,0.9076,0.3204,2.4032
|
||||||
|
33,7,0,0,uniform,15.0000,0.3000,5,1,2.6078,2.6002,2.2034,1.2034,1.2034,1.2034,1.0257,0.3629,2.7425
|
||||||
|
34,5,0,0,uniform,5.0000,0.5000,7,3,2.8112,2.8112,2.1438,1.1438,1.1438,1.1438,0.6072,0.2149,2.2006
|
||||||
|
35,3,0,0,uniform,10.0000,0.7000,3,2,2.6438,2.6417,2.1543,1.1543,1.1543,1.1543,0.8821,0.3116,1.8120
|
|
|
@ -0,0 +1,11 @@
|
||||||
|
,mean_count_firm_prod,mean_count_firm,mean_count_prod,mean_max_ts_firm_prod,mean_max_ts_firm,mean_max_ts_prod,mean_n_remove_firm_prod,mean_n_all_prod_remove_firm,mean_end_ts
|
||||||
|
prf_size,0.004,0.004,0.004,0.004,0.004,0.004,0.973,0.953,0.018
|
||||||
|
prf_conn,0.884,0.884,0.841,0.841,0.841,0.841,0.821,0.888,0.63
|
||||||
|
cap_limit_prob_type,0.708,0.723,0.517,0.517,0.517,0.517,0.002,0.001,0.002
|
||||||
|
n_max_trial,0.611,0.613,0.724,0.724,0.724,0.724,0.898,0.869,0.796
|
||||||
|
cap_limit_level,0.243,0.254,0.118,0.118,0.118,0.118,0,0,0
|
||||||
|
diff_new_conn,0.216,0.229,0.058,0.058,0.058,0.058,0.002,0.002,0
|
||||||
|
crit_supplier,0,0,0,0,0,0,0,0,0
|
||||||
|
proactive_ratio,0.66,0.651,0.572,0.572,0.572,0.572,0.258,0.399,0.367
|
||||||
|
remove_t,0.464,0.465,0.546,0.546,0.546,0.546,0.026,0.186,0
|
||||||
|
netw_prf_n,0,0,0,0,0,0,0.019,0.069,0.003
|
|
After Width: | Height: | Size: 64 KiB |
35461
analysis/count.csv
After Width: | Height: | Size: 513 KiB |
|
@ -1,98 +1,227 @@
|
||||||
up_id_product,up_name_product,down_id_product,down_name_product,count
|
up_id_product,up_name_product,down_id_product,down_name_product,count
|
||||||
1.4,工业互联网安全,1,供给,118
|
1.4,工业互联网安全,1,供给,926
|
||||||
1.4.3,网络安全,1.4,工业互联网安全,96
|
1.3,工业软件,1,供给,422
|
||||||
1.4.5,数据安全,1.4,工业互联网安全,92
|
2.1.3.5,容器服务,2.1.3,工业物联网,397
|
||||||
1.4.2,控制安全,1.4,工业互联网安全,92
|
2.1.3.4,应用管理服务,2.1.3,工业物联网,396
|
||||||
2.1,PaaS,2,工业互联网平台,77
|
2.1.3.3,工业引擎服务,2.1.3,工业物联网,396
|
||||||
1.4.4.5,安全态势感知,1.4.4,平台安全,76
|
2.1.3.6,微服务,2.1.3,工业物联网,396
|
||||||
1.3.2.1,供应链管理SCM,1.3.2,采购供应,76
|
2.1.3.1,物联网服务,2.1.3,工业物联网,390
|
||||||
1.3.2,采购供应,1.3,工业软件,74
|
2.1.3.7,制造类API,2.1.3,工业物联网,390
|
||||||
1.3.5,仓储物流,1.3,工业软件,72
|
2.1.3.2,平台基础服务,2.1.3,工业物联网,389
|
||||||
1.1.1,工业计算芯片,1.1,工业自动化,67
|
2.3.2,边缘数据处理,2.3,边缘层,332
|
||||||
1.4.5.8,数据加密,1.4.5,数据安全,50
|
2.3.1,工业数据接入,2.3,边缘层,323
|
||||||
1.4.5.1,恶意代码检测系统,1.4.5,数据安全,50
|
1.3.1.2,计算机辅助工程CAE,1.3.1,设计研发,323
|
||||||
|
2.3.3,协议转换,2.3,边缘层,321
|
||||||
|
1.3.1.1,计算机辅助设计CAD,1.3.1,设计研发,317
|
||||||
|
2.1.2.4,行业机理模型,2.1.2,工业模型库,307
|
||||||
|
1.3.1.7,电子设计自动化EDA,1.3.1,设计研发,306
|
||||||
|
1.3.1.5,产品数据管理PDM,1.3.1,设计研发,304
|
||||||
|
2.1.2.3,研发仿真模型,2.1.2,工业模型库,303
|
||||||
|
2.1.2.1,数据算法模型,2.1.2,工业模型库,302
|
||||||
|
1.3.1.3,计算机辅助制造CAM,1.3.1,设计研发,302
|
||||||
|
2.1.2.2,业务流程模型,2.1.2,工业模型库,301
|
||||||
|
1.3.1.6,产品生命周期管理PLM,1.3.1,设计研发,301
|
||||||
|
1.4.4,平台安全,1.4,工业互联网安全,301
|
||||||
|
1.3.2,采购供应,1.3,工业软件,300
|
||||||
|
1.3.1.4,计算机辅助工艺过程设计CAPP,1.3.1,设计研发,299
|
||||||
|
1.4.5,数据安全,1,供给,290
|
||||||
|
1.4.5,数据安全,1.4,工业互联网安全,290
|
||||||
|
1.1.3,工业服务器,1.1,工业自动化,278
|
||||||
|
1.1.2,工业控制器,1.1,工业自动化,276
|
||||||
|
1.1.1,工业计算芯片,1.1,工业自动化,268
|
||||||
|
1.3.1,设计研发,1.3,工业软件,241
|
||||||
|
2,工业互联网平台,1,供给,237
|
||||||
|
2.1.1.1,算法建模工具,2.1.1,开发工具,231
|
||||||
|
1.2.3,数据互通,1.2,工业互联网网络,229
|
||||||
|
2.1.1.2,低代码开发工具,2.1.1,开发工具,225
|
||||||
|
1.2.2,标识解析,1.2,工业互联网网络,222
|
||||||
|
2.1.1.4,组态建模工具,2.1.1,开发工具,221
|
||||||
|
1.2.1,网络互联,1.2,工业互联网网络,218
|
||||||
|
2.1.1.3,流程开发工具,2.1.1,开发工具,214
|
||||||
|
2.1.1.5,数字孪生建模工具,2.1.1,开发工具,212
|
||||||
|
1.4.3,网络安全,1.4,工业互联网安全,211
|
||||||
|
1.4.3,网络安全,1,供给,211
|
||||||
|
1.4.2,控制安全,1.4,工业互联网安全,205
|
||||||
|
1.4.2,控制安全,1,供给,204
|
||||||
|
1.4.4,平台安全,1,供给,199
|
||||||
|
1.3.3.4,可编程逻揖控制系统PLC,1.3.3,生产制造,177
|
||||||
|
1.3.3.1,制造执行系统MES,1.3.3,生产制造,176
|
||||||
|
1.3.3.2,分布式控制系统DCS,1.3.3,生产制造,175
|
||||||
|
1.3.3.5,企业资产管理系统EAM,1.3.3,生产制造,174
|
||||||
|
1.3.3,生产制造,1.3,工业软件,174
|
||||||
|
1.3.4.3,人力资源管理HRM,1.3.4,企业运营管理,173
|
||||||
|
1.3.4.2,客户关系管理CRM,1.3.4,企业运营管理,171
|
||||||
|
1.3.3.3,数据采集与监视控制系统SCADA,1.3.3,生产制造,170
|
||||||
|
1.3.3.6,运维保障系统MRO,1.3.3,生产制造,169
|
||||||
|
1.3.4,企业运营管理,1.3,工业软件,167
|
||||||
|
1.3.3.7,故障预测与健康管理PHM,1.3.3,生产制造,166
|
||||||
|
1.3.4.1,企业资源计划ERP,1.3.4,企业运营管理,166
|
||||||
|
2.1.4.1,工业大数据存储,2.1.4,工业大数据,161
|
||||||
|
2.1,PaaS,2,工业互联网平台,158
|
||||||
|
2.1.4.2,工业大数据管理,2.1.4,工业大数据,156
|
||||||
|
1.3.5,仓储物流,1.3,工业软件,150
|
||||||
|
1.4.4.1,身份鉴别与访问控制,1.4.4,平台安全,147
|
||||||
|
2.1.4,工业大数据,2.1,PaaS,139
|
||||||
|
1.4.4.4,工业应用行为监控,1.4.4,平台安全,136
|
||||||
|
1.4.4.2,密钥管理,1.4.4,平台安全,136
|
||||||
|
1.4.4.3,接入认证,1.4.4,平台安全,136
|
||||||
|
2.1.4.1.2,分布式数据库,2.1.4.1,工业大数据存储,130
|
||||||
|
2.1.4.1.4,时序数据库,2.1.4.1,工业大数据存储,129
|
||||||
|
2.1.4.2.1,数据质量管理,2.1.4.2,工业大数据管理,127
|
||||||
|
2.1.4.2.2,数据安全管理,2.1.4.2,工业大数据管理,125
|
||||||
|
2.1.4.1.3,实时数据库,2.1.4.1,工业大数据存储,124
|
||||||
|
2.1.4.1.1,关系型数据库,2.1.4.1,工业大数据存储,122
|
||||||
|
1.3.2,采购供应,1,供给,117
|
||||||
|
2.3,边缘层,2,工业互联网平台,109
|
||||||
|
1.4.4.5,安全态势感知,1.4.4,平台安全,100
|
||||||
|
1.3.2.1,供应链管理SCM,1.3,工业软件,100
|
||||||
|
1.3.2.1,供应链管理SCM,1.3.2,采购供应,100
|
||||||
|
2.2,IaaS,2,工业互联网平台,91
|
||||||
|
1.4.2.1,工控安全监测与审计,1.4.2,控制安全,90
|
||||||
|
1.2,工业互联网网络,1,供给,90
|
||||||
|
1.1,工业自动化,1,供给,89
|
||||||
|
2.1.4,工业大数据,2,工业互联网平台,88
|
||||||
|
2.1.3,工业物联网,2.1,PaaS,87
|
||||||
|
1.4.2.4,安全隔离与信息交换系统,1.4.2,控制安全,85
|
||||||
|
1.4.1.3,防毒墙,1.4.1,设备安全,83
|
||||||
|
1.4.1.1,工业防火墙,1.4.1,设备安全,81
|
||||||
|
2.1,PaaS,1,供给,77
|
||||||
|
1.4.3.3,APT检测,1.4.3,网络安全,76
|
||||||
|
1.3.5,仓储物流,1,供给,75
|
||||||
|
1.4.5.4,数据脱敏,1.4.5,数据安全,70
|
||||||
|
1.4.5.5,敏感数据发现与监控,1.4.5,数据安全,70
|
||||||
|
1.4.5.3,数据审计系统,1.4.5,数据安全,70
|
||||||
|
1.4.5.2,数据防泄漏系统,1.4.5,数据安全,70
|
||||||
|
1.4.5.6,数据容灾备份,1.4.5,数据安全,70
|
||||||
|
1.3.5.1,仓储物流管理WMS,1.3.5,仓储物流,70
|
||||||
|
1.4.5.7,数据恢复,1.4.5,数据安全,70
|
||||||
|
1.4.5.9,数据防火墙,1.4.5,数据安全,70
|
||||||
|
1.4.1.2,下一代防火墙,1.4.1,设备安全,68
|
||||||
|
1.4.3.5,负载均衡,1.4.3,网络安全,68
|
||||||
|
1.4.3.4,攻击溯源,1.4.3,网络安全,68
|
||||||
|
1.4.3.1,网络漏洞扫描和补丁管理,1.4.3,网络安全,68
|
||||||
|
1.4.1.5,统一威胁管理系统,1.4.1,设备安全,68
|
||||||
|
1.4.1.4,入侵检测系统,1.4.1,设备安全,68
|
||||||
|
1.4.2.2,工控主机卫士,1.4.2,控制安全,68
|
||||||
|
1.4.2.6,隐私计算,1.4.2,控制安全,68
|
||||||
|
1.4.2.5,安全日志与审计,1.4.2,控制安全,68
|
||||||
|
1.4.1,设备安全,1,供给,63
|
||||||
|
1.4.1,设备安全,1.4,工业互联网安全,63
|
||||||
|
2.1.1,开发工具,2.1,PaaS,61
|
||||||
|
2.1.2,工业模型库,2.1,PaaS,59
|
||||||
|
1.4.4.5,安全态势感知,1.4,工业互联网安全,50
|
||||||
|
1.4.4.5,安全态势感知,1,供给,50
|
||||||
1.4.3.6,沙箱类设备,1.4.3,网络安全,50
|
1.4.3.6,沙箱类设备,1.4.3,网络安全,50
|
||||||
1.4.2.7,工控原生安全,1.4.2,控制安全,50
|
1.3.5.1,仓储物流管理WMS,1.3,工业软件,50
|
||||||
|
1.4.2.3,工控漏洞扫描,1,供给,50
|
||||||
|
1.4.2.3,工控漏洞扫描,1.4,工业互联网安全,50
|
||||||
|
1.4.5.1,恶意代码检测系统,1,供给,50
|
||||||
1.4.2.3,工控漏洞扫描,1.4.2,控制安全,50
|
1.4.2.3,工控漏洞扫描,1.4.2,控制安全,50
|
||||||
1.4.1,设备安全,1.4,工业互联网安全,50
|
1.3.2.1,供应链管理SCM,1,供给,50
|
||||||
|
1.4.5.1,恶意代码检测系统,1.4,工业互联网安全,50
|
||||||
|
1.4.3.6,沙箱类设备,1.4,工业互联网安全,50
|
||||||
|
1.4.5.8,数据加密,1,供给,50
|
||||||
|
1.4.2.7,工控原生安全,1.4.2,控制安全,50
|
||||||
|
1.4.2.7,工控原生安全,1.4,工业互联网安全,50
|
||||||
|
1.4.3.2,流量检测,1,供给,50
|
||||||
|
1.4.3.2,流量检测,1.4,工业互联网安全,50
|
||||||
1.4.3.2,流量检测,1.4.3,网络安全,50
|
1.4.3.2,流量检测,1.4.3,网络安全,50
|
||||||
2.3.3,协议转换,2.3,边缘层,37
|
1.4.5.8,数据加密,1.4.5,数据安全,50
|
||||||
1.3.2.1,供应链管理SCM,1.3,工业软件,37
|
1.4.5.8,数据加密,1.4,工业互联网安全,50
|
||||||
2.3.1,工业数据接入,2.3,边缘层,33
|
1.4.3.6,沙箱类设备,1,供给,50
|
||||||
2.1.3.6,微服务,2.1.3,工业物联网,33
|
1.4.5.1,恶意代码检测系统,1.4.5,数据安全,50
|
||||||
2.3.2,边缘数据处理,2.3,边缘层,30
|
1.4.2.7,工控原生安全,1,供给,50
|
||||||
2.1.3.4,应用管理服务,2.1.3,工业物联网,30
|
2.1.4,工业大数据,1,供给,43
|
||||||
2.1.2.4,行业机理模型,2.1.2,工业模型库,30
|
1.4.4.2,密钥管理,1.4,工业互联网安全,30
|
||||||
2.1.2.2,业务流程模型,2.1.2,工业模型库,28
|
1.4.5.4,数据脱敏,1,供给,28
|
||||||
2.1.3.7,制造类API,2.1.3,工业物联网,28
|
1.4.5.4,数据脱敏,1.4,工业互联网安全,28
|
||||||
1.3.1.1,计算机辅助设计CAD,1.3.1,设计研发,28
|
1.4.4.4,工业应用行为监控,1.4,工业互联网安全,26
|
||||||
2.1.2.1,数据算法模型,2.1.2,工业模型库,27
|
1.4.5.5,敏感数据发现与监控,1,供给,25
|
||||||
1.3.1.2,计算机辅助工程CAE,1.3.1,设计研发,26
|
1.4.5.7,数据恢复,1.4,工业互联网安全,25
|
||||||
2.1.3.1,物联网服务,2.1.3,工业物联网,25
|
1.4.5.7,数据恢复,1,供给,25
|
||||||
1.1.2,工业控制器,1.1,工业自动化,24
|
1.3.5.1,仓储物流管理WMS,1,供给,25
|
||||||
2.1.3.5,容器服务,2.1.3,工业物联网,24
|
1.3.4.2,客户关系管理CRM,1.3,工业软件,25
|
||||||
1.4.3.6,沙箱类设备,1.4,工业互联网安全,23
|
1.4.5.5,敏感数据发现与监控,1.4,工业互联网安全,25
|
||||||
2.1.1.2,低代码开发工具,2.1.1,开发工具,23
|
1.3.4,企业运营管理,1,供给,24
|
||||||
1.1.3,工业服务器,1.1,工业自动化,23
|
1.4.5.9,数据防火墙,1.4,工业互联网安全,23
|
||||||
1.4.3.2,流量检测,1.4,工业互联网安全,23
|
1.4.5.9,数据防火墙,1,供给,23
|
||||||
2.1.3.3,工业引擎服务,2.1.3,工业物联网,23
|
1.4.2.5,安全日志与审计,1.4,工业互联网安全,22
|
||||||
1.4.5.1,恶意代码检测系统,1.4,工业互联网安全,21
|
1.4.2.5,安全日志与审计,1,供给,22
|
||||||
1.4.5.8,数据加密,1.4,工业互联网安全,21
|
1.3.3,生产制造,1,供给,21
|
||||||
1.4.2.3,工控漏洞扫描,1.4,工业互联网安全,21
|
1.4.4.3,接入认证,1.4,工业互联网安全,21
|
||||||
2.1.3.2,平台基础服务,2.1.3,工业物联网,21
|
1.4.5.6,数据容灾备份,1.4,工业互联网安全,21
|
||||||
1.4.2.7,工控原生安全,1.4,工业互联网安全,21
|
1.4.5.6,数据容灾备份,1,供给,21
|
||||||
1.4.3,网络安全,1,供给,21
|
1.4.3.5,负载均衡,1.4,工业互联网安全,19
|
||||||
1.3.1.4,计算机辅助工艺过程设计CAPP,1.3.1,设计研发,20
|
1.4.3.4,攻击溯源,1.4,工业互联网安全,19
|
||||||
1.4.5,数据安全,1,供给,19
|
1.4.3.1,网络漏洞扫描和补丁管理,1.4,工业互联网安全,19
|
||||||
1.4.2,控制安全,1,供给,19
|
1.4.3.1,网络漏洞扫描和补丁管理,1,供给,19
|
||||||
2.1.2.3,研发仿真模型,2.1.2,工业模型库,18
|
1.4.3.4,攻击溯源,1,供给,19
|
||||||
2.1.1.5,数字孪生建模工具,2.1.1,开发工具,18
|
2.1.4.1,工业大数据存储,2.1,PaaS,19
|
||||||
1.3.1.6,产品生命周期管理PLM,1.3.1,设计研发,18
|
1.4.3.5,负载均衡,1,供给,19
|
||||||
1.2.3,数据互通,1.2,工业互联网网络,17
|
2.1.4.2,工业大数据管理,2.1,PaaS,18
|
||||||
2.1.1.1,算法建模工具,2.1.1,开发工具,15
|
1.3.3.7,故障预测与健康管理PHM,1.3,工业软件,18
|
||||||
2.1.1.4,组态建模工具,2.1.1,开发工具,14
|
1.4.4.4,工业应用行为监控,1,供给,17
|
||||||
1.3.3.2,分布式控制系统DCS,1.3.3,生产制造,14
|
1.4.2.2,工控主机卫士,1,供给,17
|
||||||
1.2.2,标识解析,1.2,工业互联网网络,13
|
1.4.2.2,工控主机卫士,1.4,工业互联网安全,17
|
||||||
1.2.1,网络互联,1.2,工业互联网网络,13
|
2.1.4.1,工业大数据存储,2,工业互联网平台,16
|
||||||
2.1.1.3,流程开发工具,2.1.1,开发工具,12
|
1.3.4.3,人力资源管理HRM,1.3,工业软件,16
|
||||||
1.3.1.7,电子设计自动化EDA,1.3.1,设计研发,12
|
1.4.2.6,隐私计算,1,供给,15
|
||||||
1.3.3.3,数据采集与监视控制系统SCADA,1.3.3,生产制造,11
|
1.4.2.6,隐私计算,1.4,工业互联网安全,15
|
||||||
2,工业互联网平台,1,供给,10
|
1.4.5.2,数据防泄漏系统,1,供给,14
|
||||||
1.3.3.6,运维保障系统MRO,1.3.3,生产制造,10
|
2.1.4.2,工业大数据管理,2,工业互联网平台,14
|
||||||
1.3.3.1,制造执行系统MES,1.3.3,生产制造,10
|
1.3.1.5,产品数据管理PDM,1.3,工业软件,14
|
||||||
1.4.4,平台安全,1.4,工业互联网安全,10
|
1.4.5.2,数据防泄漏系统,1.4,工业互联网安全,14
|
||||||
1.4.1,设备安全,1,供给,9
|
1.3.3.3,数据采集与监视控制系统SCADA,1.3,工业软件,13
|
||||||
1.3.1,设计研发,1.3,工业软件,8
|
1.4.4.2,密钥管理,1,供给,12
|
||||||
1.3.3.4,可编程逻揖控制系统PLC,1.3.3,生产制造,7
|
1.4.4.1,身份鉴别与访问控制,1.4,工业互联网安全,12
|
||||||
1.3.4.1,企业资源计划ERP,1.3.4,企业运营管理,6
|
1.4.4.3,接入认证,1,供给,12
|
||||||
1.3.3.5,企业资产管理系统EAM,1.3.3,生产制造,6
|
1.3.1.7,电子设计自动化EDA,1.3,工业软件,12
|
||||||
1.4.3.6,沙箱类设备,1,供给,6
|
1.3.1,设计研发,1,供给,10
|
||||||
1.4.3.2,流量检测,1,供给,6
|
1.3.1.3,计算机辅助制造CAM,1.3,工业软件,10
|
||||||
1.4.5.1,恶意代码检测系统,1,供给,5
|
1.3.1.6,产品生命周期管理PLM,1.3,工业软件,10
|
||||||
1.4.4.5,安全态势感知,1.4,工业互联网安全,5
|
1.3.4.2,客户关系管理CRM,1,供给,8
|
||||||
2.1,PaaS,1,供给,5
|
2.1.2,工业模型库,2,工业互联网平台,8
|
||||||
1.4.2.7,工控原生安全,1,供给,5
|
2.1.4.1,工业大数据存储,1,供给,8
|
||||||
1.3.1.5,产品数据管理PDM,1.3.1,设计研发,5
|
1.3.3.5,企业资产管理系统EAM,1.3,工业软件,7
|
||||||
1.4.5.8,数据加密,1,供给,5
|
2.1.4.2,工业大数据管理,1,供给,7
|
||||||
1.4.2.3,工控漏洞扫描,1,供给,5
|
2.1.1,开发工具,2,工业互联网平台,6
|
||||||
2.1.4.2.2,数据安全管理,2.1.4.2,工业大数据管理,5
|
1.4.1.4,入侵检测系统,1.4,工业互联网安全,6
|
||||||
2.1.4.2.1,数据质量管理,2.1.4.2,工业大数据管理,5
|
1.4.1.4,入侵检测系统,1,供给,6
|
||||||
1.3,工业软件,1,供给,4
|
1.3.1.2,计算机辅助工程CAE,1.3,工业软件,4
|
||||||
2.1.4.1.4,时序数据库,2.1.4.1,工业大数据存储,4
|
1.4.1.5,统一威胁管理系统,1,供给,4
|
||||||
2.3,边缘层,2,工业互联网平台,3
|
1.4.4.1,身份鉴别与访问控制,1,供给,4
|
||||||
2.2,IaaS,2,工业互联网平台,3
|
2.1.3.1,物联网服务,2.1,PaaS,4
|
||||||
2.1.4.1.1,关系型数据库,2.1.4.1,工业大数据存储,3
|
1.4.3.3,APT检测,1,供给,4
|
||||||
2.1.4.1.2,分布式数据库,2.1.4.1,工业大数据存储,3
|
1.4.5.3,数据审计系统,1,供给,4
|
||||||
2.1.4.1.3,实时数据库,2.1.4.1,工业大数据存储,3
|
1.4.1.5,统一威胁管理系统,1.4,工业互联网安全,4
|
||||||
2.1.4.2,工业大数据管理,2.1.4,工业大数据,3
|
1.3.3.7,故障预测与健康管理PHM,1,供给,4
|
||||||
1.3.1.3,计算机辅助制造CAM,1.3.1,设计研发,2
|
1.3.1.4,计算机辅助工艺过程设计CAPP,1.3,工业软件,4
|
||||||
1.3.2,采购供应,1,供给,2
|
1.4.5.3,数据审计系统,1.4,工业互联网安全,4
|
||||||
1.3.3,生产制造,1.3,工业软件,1
|
1.4.3.3,APT检测,1.4,工业互联网安全,4
|
||||||
2.3.3,协议转换,2,工业互联网平台,1
|
1.2.3,数据互通,1,供给,4
|
||||||
1.3.4.3,人力资源管理HRM,1.3.4,企业运营管理,1
|
1.1.3,工业服务器,1,供给,4
|
||||||
2.1.4.1,工业大数据存储,2.1.4,工业大数据,1
|
1.3.1.1,计算机辅助设计CAD,1.3,工业软件,3
|
||||||
1.3.3.7,故障预测与健康管理PHM,1.3.3,生产制造,1
|
1.3.3.6,运维保障系统MRO,1.3,工业软件,3
|
||||||
1.3.4,企业运营管理,1.3,工业软件,1
|
1.4.1.2,下一代防火墙,1,供给,3
|
||||||
1.3.5,仓储物流,1,供给,1
|
2.1.1,开发工具,1,供给,3
|
||||||
1.4.4.1,身份鉴别与访问控制,1.4.4,平台安全,1
|
1.3.3.3,数据采集与监视控制系统SCADA,1,供给,3
|
||||||
1.3.2.1,供应链管理SCM,1,供给,1
|
2.1.3.3,工业引擎服务,2.1,PaaS,3
|
||||||
|
2.1.2,工业模型库,1,供给,3
|
||||||
|
2.1.4.1.3,实时数据库,2.1.4,工业大数据,3
|
||||||
|
1.4.1.2,下一代防火墙,1.4,工业互联网安全,3
|
||||||
|
2.1.1.3,流程开发工具,2.1,PaaS,2
|
||||||
|
2.1.4.1.2,分布式数据库,2.1.4,工业大数据,2
|
||||||
|
1.3.1.5,产品数据管理PDM,1,供给,2
|
||||||
|
2.1.3.7,制造类API,2.1,PaaS,2
|
||||||
|
1.3.3.1,制造执行系统MES,1.3,工业软件,2
|
||||||
|
1.3.3.4,可编程逻揖控制系统PLC,1.3,工业软件,2
|
||||||
|
2.1.1.4,组态建模工具,2.1,PaaS,1
|
||||||
|
2.1.2.1,数据算法模型,2.1,PaaS,1
|
||||||
|
1.3.4.3,人力资源管理HRM,1,供给,1
|
||||||
|
2.3,边缘层,1,供给,1
|
||||||
|
1.2.2,标识解析,1,供给,1
|
||||||
|
2.3.1,工业数据接入,2,工业互联网平台,1
|
||||||
|
1.2.1,网络互联,1,供给,1
|
||||||
|
2.3.2,边缘数据处理,2,工业互联网平台,1
|
||||||
|
1.3.3.5,企业资产管理系统EAM,1,供给,1
|
||||||
|
1.4.2.4,安全隔离与信息交换系统,1.4,工业互联网安全,1
|
||||||
|
|
|
After Width: | Height: | Size: 795 KiB |
|
@ -1,144 +1,172 @@
|
||||||
id_firm,Name,count
|
id_firm,Name,count
|
||||||
126,华为,468
|
126,华为,1955
|
||||||
142,深信服,300
|
170,Pseudo1,1525
|
||||||
41,启明星辰,200
|
106,阿里巴巴,1446
|
||||||
53,天融信,150
|
99,Siemens,1342
|
||||||
106,阿里巴巴,146
|
79,PTC,1271
|
||||||
170,Pseudo1,125
|
97,General Electric,991
|
||||||
99,Siemens,120
|
142,深信服,969
|
||||||
79,PTC,117
|
81,SAP,883
|
||||||
130,金蝶,91
|
41,启明星辰,842
|
||||||
13,东方国信,80
|
85,Dassault,705
|
||||||
135,浪潮,73
|
148,腾讯,697
|
||||||
23,和利时,71
|
22,航天云网,657
|
||||||
58,用友,62
|
58,用友,546
|
||||||
97,General Electric,54
|
84,Bosch,543
|
||||||
29,京东工业品,52
|
13,东方国信,501
|
||||||
63,长扬科技,50
|
80,Salesforce,499
|
||||||
85,Dassault,50
|
39,Autodesk,486
|
||||||
157,新华三,50
|
93,Cadence,485
|
||||||
140,山石网科,50
|
53,天融信,484
|
||||||
148,腾讯,49
|
73,FANUC,472
|
||||||
102,Amazon AWS,47
|
100,Synopsys,459
|
||||||
22,航天云网,46
|
75,IBM,454
|
||||||
40,奇安信,39
|
29,京东工业品,453
|
||||||
0,360科技,38
|
108,百度,441
|
||||||
98,Microsoft Azure,38
|
40,奇安信,426
|
||||||
84,Bosch,35
|
157,新华三,418
|
||||||
81,SAP,35
|
74,HoneyWell,400
|
||||||
74,HoneyWell,32
|
135,浪潮,396
|
||||||
100,Synopsys,29
|
0,360科技,352
|
||||||
86,Dell EMC,28
|
102,Amazon AWS,313
|
||||||
80,Salesforce,28
|
130,金蝶,307
|
||||||
108,百度,25
|
23,和利时,272
|
||||||
105,Intel,25
|
47,首自信,267
|
||||||
49,数码大方,24
|
26,寄云科技,252
|
||||||
47,首自信,24
|
159,徐工集团,243
|
||||||
95,Schneider,22
|
98,Microsoft Azure,233
|
||||||
39,Autodesk,21
|
77,Oracle,227
|
||||||
168,中控技术,20
|
49,数码大方,221
|
||||||
6,安世亚太,20
|
95,Schneider,216
|
||||||
16,东土科技,20
|
105,Intel,201
|
||||||
94,Mitsubishi,19
|
124,海尔,195
|
||||||
75,IBM,19
|
67,中国移动,191
|
||||||
73,FANUC,18
|
140,山石网科,190
|
||||||
124,海尔,18
|
37,绿盟,188
|
||||||
117,格创东智,17
|
155,小米,182
|
||||||
26,寄云科技,17
|
86,Dell EMC,179
|
||||||
155,小米,17
|
45,石化盈科,178
|
||||||
159,徐工集团,16
|
168,中控技术,175
|
||||||
57,亚控科技,13
|
94,Mitsubishi,174
|
||||||
149,天泽智云,13
|
117,格创东智,160
|
||||||
93,Cadence,13
|
115,富士康,155
|
||||||
62,云道智造,13
|
55,威努特,153
|
||||||
82,Uptake,12
|
6,安世亚太,148
|
||||||
78,OutSystems,12
|
5,安华金和,128
|
||||||
161,研华科技,12
|
143,沈阳自动化研究所,126
|
||||||
60,宇动源,11
|
3,艾克斯特,124
|
||||||
165,智能云科,11
|
62,云道智造,119
|
||||||
33,蓝谷信息,10
|
78,OutSystems,115
|
||||||
42,山大华天,10
|
38,牛刀,112
|
||||||
67,中国移动,10
|
33,蓝谷信息,111
|
||||||
131,九物互联,10
|
42,山大华天,109
|
||||||
38,牛刀,10
|
60,宇动源,107
|
||||||
103,STMicroelectronics ,9
|
57,亚控科技,107
|
||||||
144,树根互联,9
|
165,智能云科,106
|
||||||
56,芯愿景,8
|
144,树根互联,106
|
||||||
143,沈阳自动化研究所,8
|
16,东土科技,104
|
||||||
127,华为海思,8
|
31,昆仑数据,103
|
||||||
153,武汉开目,8
|
68,中望软件,101
|
||||||
3,艾克斯特,7
|
82,Uptake,100
|
||||||
45,石化盈科,7
|
149,天泽智云,98
|
||||||
68,中望软件,7
|
137,美林数据,93
|
||||||
31,昆仑数据,6
|
163,优也科技,92
|
||||||
46,适创科技,6
|
154,西格数据,92
|
||||||
111,鼎捷软件,6
|
161,研华科技,90
|
||||||
89,Rockwell,6
|
131,九物互联,86
|
||||||
150,唯捷创芯,6
|
111,鼎捷软件,79
|
||||||
169,中芯国际,6
|
63,长扬科技,76
|
||||||
69,紫光集团,5
|
43,神舟软件,75
|
||||||
113,飞腾信息,5
|
14,东华软件,72
|
||||||
167,中环股份,5
|
162,壹进制,70
|
||||||
129,华中数控,5
|
153,武汉开目,69
|
||||||
43,神舟软件,5
|
54,网御星云,68
|
||||||
71,Altair,4
|
9,北京航天测控,65
|
||||||
104,Infineon,4
|
89,Rockwell,64
|
||||||
77,Oracle,4
|
133,蓝盾股份,52
|
||||||
123,海得控制,4
|
70,ABB,51
|
||||||
145,思普软件,4
|
129,华中数控,47
|
||||||
35,凌昊智能,4
|
127,华为海思,47
|
||||||
163,优也科技,4
|
56,芯愿景,46
|
||||||
24,华大电子,4
|
27,江南天安,45
|
||||||
32,兰光创新,4
|
76,MasterCAM,45
|
||||||
115,富士康,4
|
11,北信源,45
|
||||||
147,拓邦股份,4
|
50,索为系统,45
|
||||||
9,北京航天测控,3
|
96,Cisco,45
|
||||||
88,HPE,3
|
116,概伦电子,44
|
||||||
87,Texas Instruments,3
|
152,卫士通,43
|
||||||
120,广州数控,3
|
138,启明信息,43
|
||||||
12,大唐软件,3
|
90,Mentor Graphics,42
|
||||||
64,中电智科,3
|
21,Hexagon,42
|
||||||
90,Mentor Graphics,3
|
112,东华测试,41
|
||||||
101,Analog Devices,3
|
25,华大九天,39
|
||||||
116,概伦电子,3
|
71,Altair,38
|
||||||
166,中国电子科技网络信息安全,3
|
158,信大捷安,38
|
||||||
119,广联达,3
|
72,ANSYS,38
|
||||||
70,ABB,3
|
146,苏州浩辰,38
|
||||||
20,海基科技,3
|
48,曙光信息,38
|
||||||
65,中国电信,3
|
46,适创科技,38
|
||||||
72,ANSYS,3
|
88,HPE,37
|
||||||
4,爱创科技,3
|
139,容知日新,37
|
||||||
36,龙芯中科,3
|
156,芯禾科技,37
|
||||||
44,圣邦微电子,3
|
15,东软集团,36
|
||||||
146,苏州浩辰,3
|
20,海基科技,36
|
||||||
14,东华软件,3
|
120,广州数控,36
|
||||||
83,Emerson,2
|
10,北京英贝思,36
|
||||||
138,启明信息,2
|
145,思普软件,35
|
||||||
10,北京英贝思,2
|
151,唯智信息,35
|
||||||
128,华伍股份,2
|
52,天空卫士,35
|
||||||
15,东软集团,2
|
119,广联达,35
|
||||||
154,西格数据,2
|
114,富勒科技,35
|
||||||
156,芯禾科技,2
|
92,Omron,34
|
||||||
48,曙光信息,2
|
30,可信华泰,34
|
||||||
50,索为系统,2
|
4,爱创科技,34
|
||||||
141,上海新华控制,2
|
109,宝信软件,34
|
||||||
61,元年科技,2
|
110,晨科软件,34
|
||||||
164,震坤行,2
|
122,国民技术,34
|
||||||
2,706所,2
|
59,优特捷,34
|
||||||
134,朗坤智慧,2
|
164,震坤行,34
|
||||||
137,美林数据,2
|
61,元年科技,33
|
||||||
25,华大九天,2
|
147,拓邦股份,33
|
||||||
34,力控科技,2
|
160,亚信科技,33
|
||||||
132,科远智慧,1
|
107,安恒信息,33
|
||||||
92,Omron,1
|
2,706所,33
|
||||||
21,Hexagon,1
|
134,朗坤智慧,32
|
||||||
96,Cisco,1
|
35,凌昊智能,32
|
||||||
18,国能智深,1
|
1,51WORLD,31
|
||||||
118,工邦邦,1
|
64,中电智科,31
|
||||||
91,Moxa,1
|
118,工邦邦,31
|
||||||
125,华数机器人,1
|
166,中国电子科技网络信息安全,31
|
||||||
133,蓝盾股份,1
|
34,力控科技,31
|
||||||
109,宝信软件,1
|
8,梆梆安全,30
|
||||||
139,容知日新,1
|
125,华数机器人,30
|
||||||
66,中国联通,1
|
128,华伍股份,29
|
||||||
1,51WORLD,1
|
66,中国联通,28
|
||||||
|
123,海得控制,28
|
||||||
|
32,兰光创新,28
|
||||||
|
17,国保金泰,28
|
||||||
|
51,天地和兴,28
|
||||||
|
19,国泰网信,28
|
||||||
|
121,广州智臣,28
|
||||||
|
12,大唐软件,27
|
||||||
|
132,科远智慧,27
|
||||||
|
83,Emerson,27
|
||||||
|
65,中国电信,25
|
||||||
|
7,百望,24
|
||||||
|
136,美的,24
|
||||||
|
141,上海新华控制,24
|
||||||
|
18,国能智深,24
|
||||||
|
169,中芯国际,22
|
||||||
|
44,圣邦微电子,21
|
||||||
|
103,STMicroelectronics ,21
|
||||||
|
167,中环股份,21
|
||||||
|
36,龙芯中科,21
|
||||||
|
91,Moxa,20
|
||||||
|
28,金山云,20
|
||||||
|
69,紫光集团,20
|
||||||
|
113,飞腾信息,19
|
||||||
|
87,Texas Instruments,18
|
||||||
|
104,Infineon,18
|
||||||
|
101,Analog Devices,18
|
||||||
|
24,华大电子,17
|
||||||
|
150,唯捷创芯,17
|
||||||
|
|
|
|
@ -1,358 +1,476 @@
|
||||||
id_firm,name_firm,id_product,name_product,count
|
id_firm,name_firm,id_product,name_product,count
|
||||||
126,华为,1.4,工业互联网安全,385
|
170,Pseudo1,1,供给,1525
|
||||||
142,深信服,1.4.3,网络安全,150
|
126,华为,1.4,工业互联网安全,1012
|
||||||
41,启明星辰,1.4.5,数据安全,150
|
41,启明星辰,1.4.5,数据安全,640
|
||||||
142,深信服,1.4.2,控制安全,150
|
142,深信服,1.4.2,控制安全,529
|
||||||
170,Pseudo1,1,供给,125
|
39,Autodesk,1.3.1,设计研发,486
|
||||||
106,阿里巴巴,1.3,工业软件,67
|
93,Cadence,1.3.1,设计研发,485
|
||||||
29,京东工业品,1.3,工业软件,52
|
73,FANUC,2.1.3,工业物联网,472
|
||||||
53,天融信,1.4.2.3,工控漏洞扫描,50
|
100,Synopsys,1.3.1,设计研发,459
|
||||||
41,启明星辰,1.4.3.2,流量检测,50
|
75,IBM,1.3.3,生产制造,454
|
||||||
|
29,京东工业品,1.3,工业软件,453
|
||||||
|
108,百度,2.1.3,工业物联网,434
|
||||||
|
106,阿里巴巴,1.3,工业软件,433
|
||||||
|
142,深信服,1.4.3,网络安全,430
|
||||||
|
97,General Electric,1.3.3,生产制造,424
|
||||||
|
99,Siemens,1.3.3,生产制造,418
|
||||||
|
157,新华三,1.4.1,设备安全,418
|
||||||
|
85,Dassault,1.3.1,设计研发,412
|
||||||
|
99,Siemens,1.3.1,设计研发,404
|
||||||
|
148,腾讯,2.1.3,工业物联网,402
|
||||||
|
97,General Electric,2.1.3,工业物联网,385
|
||||||
|
74,HoneyWell,2.1.3,工业物联网,383
|
||||||
|
106,阿里巴巴,2.1.3,工业物联网,372
|
||||||
|
126,华为,2.1.3,工业物联网,362
|
||||||
|
40,奇安信,1.4.4,平台安全,357
|
||||||
|
0,360科技,1.4.4,平台安全,352
|
||||||
|
99,Siemens,2.1,PaaS,323
|
||||||
|
79,PTC,2.1.4.1,工业大数据存储,317
|
||||||
|
80,Salesforce,2.1.1,开发工具,310
|
||||||
|
85,Dassault,2.1.1,开发工具,293
|
||||||
|
148,腾讯,2.1.1,开发工具,285
|
||||||
|
58,用友,2.1.2,工业模型库,281
|
||||||
|
79,PTC,2.1.2,工业模型库,280
|
||||||
|
81,SAP,2.1.4.1,工业大数据存储,278
|
||||||
|
106,阿里巴巴,2.1.1,开发工具,271
|
||||||
|
159,徐工集团,2.1.2,工业模型库,243
|
||||||
|
81,SAP,2.1.2,工业模型库,235
|
||||||
|
98,Microsoft Azure,2,工业互联网平台,233
|
||||||
|
84,Bosch,2.1.2,工业模型库,230
|
||||||
|
81,SAP,1.3.4,企业运营管理,209
|
||||||
|
102,Amazon AWS,2,工业互联网平台,203
|
||||||
|
105,Intel,1.1,工业自动化,201
|
||||||
|
77,Oracle,1.3.4,企业运营管理,194
|
||||||
|
67,中国移动,1.2,工业互联网网络,191
|
||||||
|
126,华为,1.2,工业互联网网络,190
|
||||||
|
95,Schneider,2.3,边缘层,190
|
||||||
|
80,Salesforce,1.3.4,企业运营管理,189
|
||||||
|
106,阿里巴巴,1.2,工业互联网网络,188
|
||||||
|
84,Bosch,2.3,边缘层,182
|
||||||
|
97,General Electric,1.2,工业互联网网络,182
|
||||||
|
155,小米,2.3,边缘层,182
|
||||||
|
79,PTC,2.1.4.2,工业大数据管理,181
|
||||||
|
124,海尔,2.3,边缘层,179
|
||||||
|
86,Dell EMC,1.1,工业自动化,179
|
||||||
|
126,华为,1.1,工业自动化,178
|
||||||
|
94,Mitsubishi,1.1,工业自动化,174
|
||||||
|
126,华为,2.3,边缘层,174
|
||||||
|
106,阿里巴巴,1.1,工业自动化,172
|
||||||
|
99,Siemens,2.3,边缘层,166
|
||||||
|
81,SAP,2.1.4.2,工业大数据管理,161
|
||||||
|
115,富士康,2.1.4,工业大数据,131
|
||||||
|
84,Bosch,2.1.4,工业大数据,131
|
||||||
|
130,金蝶,1.3.5,仓储物流,120
|
||||||
|
102,Amazon AWS,2.1.4,工业大数据,110
|
||||||
|
130,金蝶,1.3.2,采购供应,88
|
||||||
|
58,用友,1.3.2,采购供应,88
|
||||||
23,和利时,1.4.2.7,工控原生安全,50
|
23,和利时,1.4.2.7,工控原生安全,50
|
||||||
63,长扬科技,1.4.4.5,安全态势感知,50
|
|
||||||
157,新华三,1.4.1,设备安全,50
|
|
||||||
53,天融信,1.4.5.8,数据加密,50
|
|
||||||
140,山石网科,1.4.5.1,恶意代码检测系统,50
|
|
||||||
135,浪潮,1.3.2.1,供应链管理SCM,50
|
|
||||||
130,金蝶,1.3.5,仓储物流,50
|
|
||||||
99,Siemens,2.1,PaaS,50
|
|
||||||
53,天融信,1.4.3.6,沙箱类设备,50
|
53,天融信,1.4.3.6,沙箱类设备,50
|
||||||
102,Amazon AWS,2,工业互联网平台,45
|
53,天融信,1.4.2.3,工控漏洞扫描,50
|
||||||
130,金蝶,1.3.2,采购供应,40
|
63,长扬科技,1.4.4.5,安全态势感知,50
|
||||||
40,奇安信,1.4.4,平台安全,39
|
135,浪潮,1.3.2.1,供应链管理SCM,50
|
||||||
0,360科技,1.4.4,平台安全,38
|
41,启明星辰,1.4.3.2,流量检测,50
|
||||||
98,Microsoft Azure,2,工业互联网平台,38
|
140,山石网科,1.4.5.1,恶意代码检测系统,50
|
||||||
58,用友,1.3.2,采购供应,36
|
53,天融信,1.4.5.8,数据加密,50
|
||||||
148,腾讯,2.1.3,工业物联网,32
|
13,东方国信,2.1.3.4,应用管理服务,46
|
||||||
74,HoneyWell,2.1.3,工业物联网,30
|
54,网御星云,1.4.4.3,接入认证,45
|
||||||
100,Synopsys,1.3.1,设计研发,29
|
53,天融信,1.4.4.4,工业应用行为监控,45
|
||||||
85,Dassault,1.3.1,设计研发,29
|
11,北信源,1.4.4.2,密钥管理,45
|
||||||
86,Dell EMC,1.1,工业自动化,28
|
76,MasterCAM,1.3.1.3,计算机辅助制造CAM,45
|
||||||
99,Siemens,1.3.1,设计研发,27
|
50,索为系统,1.3.1.5,产品数据管理PDM,45
|
||||||
97,General Electric,2.1.3,工业物联网,27
|
37,绿盟,1.4.4.3,接入认证,45
|
||||||
106,阿里巴巴,2.1.3,工业物联网,27
|
79,PTC,2.1.3.2,平台基础服务,45
|
||||||
126,华为,2.1.3,工业物联网,26
|
55,威努特,1.4.4.4,工业应用行为监控,45
|
||||||
105,Intel,1.1,工业自动化,25
|
27,江南天安,1.4.4.2,密钥管理,45
|
||||||
80,Salesforce,2.1.1,开发工具,25
|
116,概伦电子,1.3.1.7,电子设计自动化EDA,44
|
||||||
79,PTC,2.1.2,工业模型库,25
|
135,浪潮,2.1.3.2,平台基础服务,44
|
||||||
108,百度,2.1.3,工业物联网,24
|
79,PTC,2.1.3.1,物联网服务,44
|
||||||
84,Bosch,2.1.2,工业模型库,22
|
135,浪潮,2.1.3.3,工业引擎服务,44
|
||||||
58,用友,2.1.2,工业模型库,22
|
152,卫士通,1.4.4.1,身份鉴别与访问控制,43
|
||||||
39,Autodesk,1.3.1,设计研发,21
|
22,航天云网,2.1.3.4,应用管理服务,43
|
||||||
97,General Electric,1.3.3,生产制造,21
|
22,航天云网,2.1.3.5,容器服务,43
|
||||||
106,阿里巴巴,1.1,工业自动化,21
|
22,航天云网,2.1.3.3,工业引擎服务,43
|
||||||
85,Dassault,2.1.1,开发工具,21
|
13,东方国信,2.1.3.1,物联网服务,43
|
||||||
126,华为,1.1,工业自动化,21
|
79,PTC,2.1.3.5,容器服务,43
|
||||||
99,Siemens,1.3.3,生产制造,20
|
79,PTC,2.1.3.4,应用管理服务,43
|
||||||
99,Siemens,2.3,边缘层,20
|
14,东华软件,1.3.4.3,人力资源管理HRM,43
|
||||||
106,阿里巴巴,2.1.1,开发工具,19
|
13,东方国信,2.1.3.7,制造类API,43
|
||||||
126,华为,2.3,边缘层,19
|
22,航天云网,2.1.3.7,制造类API,43
|
||||||
75,IBM,1.3.3,生产制造,19
|
13,东方国信,2.1.3.5,容器服务,43
|
||||||
94,Mitsubishi,1.1,工业自动化,19
|
138,启明信息,1.3.1.5,产品数据管理PDM,43
|
||||||
73,FANUC,2.1.3,工业物联网,18
|
13,东方国信,2.1.3.2,平台基础服务,43
|
||||||
81,SAP,2.1.2,工业模型库,18
|
13,东方国信,2.1.3.3,工业引擎服务,43
|
||||||
95,Schneider,2.3,边缘层,18
|
21,Hexagon,1.3.1.3,计算机辅助制造CAM,42
|
||||||
155,小米,2.3,边缘层,17
|
135,浪潮,2.1.3.7,制造类API,42
|
||||||
148,腾讯,2.1.1,开发工具,17
|
90,Mentor Graphics,1.3.1.7,电子设计自动化EDA,42
|
||||||
124,海尔,2.3,边缘层,16
|
79,PTC,2.1.3.3,工业引擎服务,42
|
||||||
159,徐工集团,2.1.2,工业模型库,16
|
135,浪潮,2.1.3.5,容器服务,42
|
||||||
126,华为,1.2,工业互联网网络,15
|
79,PTC,2.1.3.7,制造类API,42
|
||||||
93,Cadence,1.3.1,设计研发,13
|
135,浪潮,2.1.3.1,物联网服务,42
|
||||||
106,阿里巴巴,1.2,工业互联网网络,12
|
79,PTC,2.1.3.6,微服务,42
|
||||||
84,Bosch,2.3,边缘层,12
|
112,东华测试,1.3.3.7,故障预测与健康管理PHM,41
|
||||||
13,东方国信,2.1.3.7,制造类API,11
|
26,寄云科技,2.1.3.4,应用管理服务,41
|
||||||
13,东方国信,2.1.3.4,应用管理服务,11
|
22,航天云网,2.1.3.1,物联网服务,41
|
||||||
13,东方国信,2.1.3.5,容器服务,10
|
45,石化盈科,1.3.4.2,客户关系管理CRM,41
|
||||||
79,PTC,2.1.3.2,平台基础服务,10
|
22,航天云网,2.1.3.2,平台基础服务,40
|
||||||
67,中国移动,1.2,工业互联网网络,10
|
43,神舟软件,1.3.1.5,产品数据管理PDM,40
|
||||||
79,PTC,2.1.3.1,物联网服务,9
|
42,山大华天,1.3.1.3,计算机辅助制造CAM,40
|
||||||
79,PTC,2.1.3.4,应用管理服务,9
|
58,用友,1.3.4.3,人力资源管理HRM,40
|
||||||
103,STMicroelectronics ,1.1.1,工业计算芯片,9
|
130,金蝶,1.3.4.2,客户关系管理CRM,40
|
||||||
13,东方国信,2.1.3.1,物联网服务,9
|
26,寄云科技,2.1.3.5,容器服务,40
|
||||||
13,东方国信,2.1.3.3,工业引擎服务,8
|
26,寄云科技,2.1.3.2,平台基础服务,40
|
||||||
79,PTC,2.1.3.5,容器服务,8
|
58,用友,1.3.4.2,客户关系管理CRM,40
|
||||||
79,PTC,2.1.4.1,工业大数据存储,7
|
56,芯愿景,1.3.1.7,电子设计自动化EDA,39
|
||||||
13,东方国信,2.1.3.6,微服务,7
|
25,华大九天,1.3.1.7,电子设计自动化EDA,39
|
||||||
79,PTC,2.1.3.7,制造类API,7
|
68,中望软件,1.3.1.3,计算机辅助制造CAM,39
|
||||||
81,SAP,2.1.4.1,工业大数据存储,7
|
72,ANSYS,1.3.1.2,计算机辅助工程CAE,38
|
||||||
81,SAP,2.1.4.2,工业大数据管理,7
|
48,曙光信息,1.2.2,标识解析,38
|
||||||
79,PTC,2.1.3.6,微服务,7
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,38
|
||||||
79,PTC,2.3.3,协议转换,6
|
135,浪潮,2.1.3.4,应用管理服务,38
|
||||||
79,PTC,2.1.3.3,工业引擎服务,6
|
133,蓝盾股份,1.4.4.1,身份鉴别与访问控制,38
|
||||||
16,东土科技,2.3.1,工业数据接入,6
|
3,艾克斯特,1.3.1.5,产品数据管理PDM,38
|
||||||
150,唯捷创芯,1.1.1,工业计算芯片,6
|
130,金蝶,1.3.4.3,人力资源管理HRM,38
|
||||||
49,数码大方,1.3.1.1,计算机辅助设计CAD,6
|
71,Altair,1.3.1.2,计算机辅助工程CAE,38
|
||||||
79,PTC,2.3.1,工业数据接入,6
|
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,38
|
||||||
47,首自信,2.1.3.6,微服务,6
|
158,信大捷安,1.4.4.1,身份鉴别与访问控制,38
|
||||||
56,芯愿景,1.1.1,工业计算芯片,6
|
22,航天云网,2.1.3.6,微服务,38
|
||||||
169,中芯国际,1.1.1,工业计算芯片,6
|
58,用友,1.3.1.6,产品生命周期管理PLM,38
|
||||||
97,General Electric,1.2,工业互联网网络,6
|
9,北京航天测控,1.3.3.7,故障预测与健康管理PHM,38
|
||||||
46,适创科技,1.3.1.2,计算机辅助工程CAE,6
|
23,和利时,2.1.3.6,微服务,38
|
||||||
47,首自信,2.1.2.1,数据算法模型,6
|
88,HPE,1.1.3,工业服务器,37
|
||||||
13,东方国信,2.1.3.2,平台基础服务,6
|
139,容知日新,1.3.3.7,故障预测与健康管理PHM,37
|
||||||
16,东土科技,1.1.3,工业服务器,5
|
156,芯禾科技,1.3.1.7,电子设计自动化EDA,37
|
||||||
161,研华科技,2.3.3,协议转换,5
|
58,用友,1.2.2,标识解析,36
|
||||||
16,东土科技,2.3.3,协议转换,5
|
120,广州数控,1.2.3,数据互通,36
|
||||||
22,航天云网,2.1.3.6,微服务,5
|
10,北京英贝思,1.3.3.5,企业资产管理系统EAM,36
|
||||||
168,中控技术,2.3.3,协议转换,5
|
153,武汉开目,1.3.1.4,计算机辅助工艺过程设计CAPP,36
|
||||||
13,东方国信,2.3.2,边缘数据处理,5
|
79,PTC,1.3.1.4,计算机辅助工艺过程设计CAPP,36
|
||||||
22,航天云网,2.3.1,工业数据接入,5
|
15,东软集团,1.3.3.5,企业资产管理系统EAM,36
|
||||||
153,武汉开目,1.3.1.1,计算机辅助设计CAD,5
|
20,海基科技,1.3.1.2,计算机辅助工程CAE,36
|
||||||
69,紫光集团,1.1.1,工业计算芯片,5
|
26,寄云科技,2.1.3.7,制造类API,36
|
||||||
22,航天云网,2.3.3,协议转换,5
|
135,浪潮,2.1.3.6,微服务,36
|
||||||
127,华为海思,1.1.1,工业计算芯片,5
|
26,寄云科技,2.1.3.3,工业引擎服务,35
|
||||||
6,安世亚太,2.1.2.1,数据算法模型,5
|
42,山大华天,1.3.1.1,计算机辅助设计CAD,35
|
||||||
79,PTC,2.1.4.2,工业大数据管理,5
|
162,壹进制,1.4.5.7,数据恢复,35
|
||||||
23,和利时,2.3.3,协议转换,5
|
37,绿盟,1.4.5.2,数据防泄漏系统,35
|
||||||
42,山大华天,1.3.1.1,计算机辅助设计CAD,5
|
162,壹进制,1.4.5.6,数据容灾备份,35
|
||||||
113,飞腾信息,1.1.1,工业计算芯片,5
|
119,广联达,1.3.1.1,计算机辅助设计CAD,35
|
||||||
167,中环股份,1.1.1,工业计算芯片,5
|
43,神舟软件,1.3.1.6,产品生命周期管理PLM,35
|
||||||
78,OutSystems,2.1.1.5,数字孪生建模工具,4
|
140,山石网科,1.4.5.4,数据脱敏,35
|
||||||
32,兰光创新,1.2.3,数据互通,4
|
168,中控技术,2.3.1,工业数据接入,35
|
||||||
68,中望软件,1.3.1.2,计算机辅助工程CAE,4
|
114,富勒科技,1.3.5.1,仓储物流管理WMS,35
|
||||||
78,OutSystems,2.1.1.2,低代码开发工具,4
|
140,山石网科,1.4.5.9,数据防火墙,35
|
||||||
6,安世亚太,2.1.2.4,行业机理模型,4
|
53,天融信,1.4.5.7,数据恢复,35
|
||||||
165,智能云科,2.1.2.2,业务流程模型,4
|
5,安华金和,1.4.5.5,敏感数据发现与监控,35
|
||||||
24,华大电子,1.1.1,工业计算芯片,4
|
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,35
|
||||||
62,云道智造,2.1.2.2,业务流程模型,4
|
53,天融信,1.4.5.2,数据防泄漏系统,35
|
||||||
23,和利时,2.3.2,边缘数据处理,4
|
5,安华金和,1.4.5.9,数据防火墙,35
|
||||||
16,东土科技,2.3.2,边缘数据处理,4
|
151,唯智信息,1.3.5.1,仓储物流管理WMS,35
|
||||||
6,安世亚太,2.1.2.3,研发仿真模型,4
|
53,天融信,1.4.5.6,数据容灾备份,35
|
||||||
22,航天云网,2.1.3.4,应用管理服务,4
|
52,天空卫士,1.4.5.5,敏感数据发现与监控,35
|
||||||
71,Altair,1.3.1.2,计算机辅助工程CAE,4
|
5,安华金和,1.4.5.4,数据脱敏,35
|
||||||
161,研华科技,2.3.2,边缘数据处理,4
|
47,首自信,2.1.3.6,微服务,35
|
||||||
168,中控技术,2.3.2,边缘数据处理,4
|
92,Omron,1.3.3.4,可编程逻揖控制系统PLC,34
|
||||||
35,凌昊智能,1.1.3,工业服务器,4
|
55,威努特,1.4.2.2,工控主机卫士,34
|
||||||
33,蓝谷信息,2.1.2.4,行业机理模型,4
|
79,PTC,2.3.1,工业数据接入,34
|
||||||
57,亚控科技,2.3.3,协议转换,4
|
6,安世亚太,1.3.1.2,计算机辅助工程CAE,34
|
||||||
129,华中数控,1.1.2,工业控制器,4
|
109,宝信软件,1.3.3.1,制造执行系统MES,34
|
||||||
13,东方国信,2.3.1,工业数据接入,4
|
59,优特捷,1.4.2.5,安全日志与审计,34
|
||||||
104,Infineon,1.1.1,工业计算芯片,4
|
53,天融信,1.4.3.5,负载均衡,34
|
||||||
131,九物互联,2.1.1.2,低代码开发工具,4
|
53,天融信,1.4.3.4,攻击溯源,34
|
||||||
95,Schneider,1.2.3,数据互通,4
|
30,可信华泰,1.4.2.6,隐私计算,34
|
||||||
149,天泽智云,2.1.2.4,行业机理模型,4
|
122,国民技术,1.4.2.6,隐私计算,34
|
||||||
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,4
|
37,绿盟,1.4.3.1,网络漏洞扫描和补丁管理,34
|
||||||
135,浪潮,2.1.3.7,制造类API,4
|
110,晨科软件,1.3.3.5,企业资产管理系统EAM,34
|
||||||
117,格创东智,2.1.1.4,组态建模工具,4
|
37,绿盟,1.4.2.2,工控主机卫士,34
|
||||||
82,Uptake,2.1.2.4,行业机理模型,4
|
4,爱创科技,1.2.2,标识解析,34
|
||||||
57,亚控科技,2.3.2,边缘数据处理,4
|
40,奇安信,1.4.2.5,安全日志与审计,34
|
||||||
43,神舟软件,1.3.1.6,产品生命周期管理PLM,4
|
47,首自信,2.1.1.2,低代码开发工具,34
|
||||||
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,4
|
41,启明星辰,1.4.3.1,网络漏洞扫描和补丁管理,34
|
||||||
123,海得控制,1.1.2,工业控制器,4
|
41,启明星辰,1.4.3.4,攻击溯源,34
|
||||||
38,牛刀,2.1.1.5,数字孪生建模工具,4
|
41,启明星辰,1.4.3.5,负载均衡,34
|
||||||
149,天泽智云,2.1.2.3,研发仿真模型,4
|
164,震坤行,1.3.3.6,运维保障系统MRO,34
|
||||||
147,拓邦股份,1.1.2,工业控制器,4
|
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,34
|
||||||
6,安世亚太,2.1.2.2,业务流程模型,4
|
2,706所,1.1.3,工业服务器,33
|
||||||
4,爱创科技,1.2.2,标识解析,3
|
107,安恒信息,1.4.3.3,APT检测,33
|
||||||
36,龙芯中科,1.1.1,工业计算芯片,3
|
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,33
|
||||||
33,蓝谷信息,2.1.2.2,业务流程模型,3
|
49,数码大方,1.3.1.6,产品生命周期管理PLM,33
|
||||||
115,富士康,1.1.3,工业服务器,3
|
13,东方国信,2.1.3.6,微服务,33
|
||||||
49,数码大方,2.1.2.1,数据算法模型,3
|
160,亚信科技,1.4.1.3,防毒墙,33
|
||||||
49,数码大方,1.3.3.1,制造执行系统MES,3
|
61,元年科技,1.3.3.3,数据采集与监视控制系统SCADA,33
|
||||||
23,和利时,2.1.3.6,微服务,3
|
26,寄云科技,2.1.3.1,物联网服务,33
|
||||||
49,数码大方,2.1.2.2,业务流程模型,3
|
68,中望软件,1.3.1.1,计算机辅助设计CAD,33
|
||||||
64,中电智科,1.1.2,工业控制器,3
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,33
|
||||||
49,数码大方,1.3.1.6,产品生命周期管理PLM,3
|
147,拓邦股份,1.1.2,工业控制器,33
|
||||||
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
79,PTC,1.3.1.1,计算机辅助设计CAD,33
|
||||||
47,首自信,2.1.2.4,行业机理模型,3
|
3,艾克斯特,1.3.1.4,计算机辅助工艺过程设计CAPP,33
|
||||||
47,首自信,2.1.1.2,低代码开发工具,3
|
77,Oracle,1.3.3.6,运维保障系统MRO,33
|
||||||
62,云道智造,2.1.2.4,行业机理模型,3
|
23,和利时,2.3.2,边缘数据处理,32
|
||||||
117,格创东智,2.1.1.2,低代码开发工具,3
|
6,安世亚太,2.1.2.4,行业机理模型,32
|
||||||
60,宇动源,2.1.1.1,算法建模工具,3
|
79,PTC,1.3.1.6,产品生命周期管理PLM,32
|
||||||
26,寄云科技,2.1.3.1,物联网服务,3
|
47,首自信,2.1.2.3,研发仿真模型,32
|
||||||
117,格创东智,2.1.1.1,算法建模工具,3
|
35,凌昊智能,1.1.3,工业服务器,32
|
||||||
26,寄云科技,2.1.3.3,工业引擎服务,3
|
134,朗坤智慧,1.3.3.5,企业资产管理系统EAM,32
|
||||||
44,圣邦微电子,1.1.1,工业计算芯片,3
|
168,中控技术,2.3.3,协议转换,32
|
||||||
62,云道智造,1.3.1.2,计算机辅助工程CAE,3
|
127,华为海思,1.1.3,工业服务器,32
|
||||||
26,寄云科技,2.1.3.6,微服务,3
|
118,工邦邦,1.3.3.6,运维保障系统MRO,31
|
||||||
6,安世亚太,1.3.1.2,计算机辅助工程CAE,3
|
64,中电智科,1.1.2,工业控制器,31
|
||||||
57,亚控科技,2.3.1,工业数据接入,3
|
13,东方国信,2.3.1,工业数据接入,31
|
||||||
3,艾克斯特,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
161,研华科技,2.3.1,工业数据接入,31
|
||||||
116,概伦电子,1.3.1.7,电子设计自动化EDA,3
|
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,31
|
||||||
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,3
|
111,鼎捷软件,1.3.1.6,产品生命周期管理PLM,31
|
||||||
31,昆仑数据,1.3.3.3,数据采集与监视控制系统SCADA,3
|
1,51WORLD,2.1.1.5,数字孪生建模工具,31
|
||||||
60,宇动源,2.1.1.2,低代码开发工具,3
|
22,航天云网,2.3.2,边缘数据处理,31
|
||||||
65,中国电信,1.2.1,网络互联,3
|
70,ABB,1.3.3.4,可编程逻揖控制系统PLC,31
|
||||||
23,和利时,2.3.1,工业数据接入,3
|
144,树根互联,2.1.2.1,数据算法模型,31
|
||||||
68,中望软件,1.3.1.1,计算机辅助设计CAD,3
|
34,力控科技,1.3.3.3,数据采集与监视控制系统SCADA,31
|
||||||
87,Texas Instruments,1.1.1,工业计算芯片,3
|
143,沈阳自动化研究所,2.1.1.4,组态建模工具,31
|
||||||
149,天泽智云,2.1.2.2,业务流程模型,3
|
166,中国电子科技网络信息安全,1.2.3,数据互通,31
|
||||||
120,广州数控,1.2.3,数据互通,3
|
57,亚控科技,2.3.1,工业数据接入,31
|
||||||
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,3
|
161,研华科技,2.3.3,协议转换,31
|
||||||
144,树根互联,2.1.2.4,行业机理模型,3
|
47,首自信,2.1.2.4,行业机理模型,30
|
||||||
22,航天云网,2.1.3.7,制造类API,3
|
49,数码大方,2.1.2.3,研发仿真模型,30
|
||||||
80,Salesforce,1.3.4,企业运营管理,3
|
47,首自信,2.1.2.2,业务流程模型,30
|
||||||
81,SAP,1.3.4,企业运营管理,3
|
13,东方国信,2.3.2,边缘数据处理,30
|
||||||
82,Uptake,2.1.2.1,数据算法模型,3
|
13,东方国信,1.2.2,标识解析,30
|
||||||
82,Uptake,2.1.2.2,业务流程模型,3
|
79,PTC,2.3.2,边缘数据处理,30
|
||||||
111,鼎捷软件,1.3.1.6,产品生命周期管理PLM,3
|
8,梆梆安全,1.4.1.1,工业防火墙,30
|
||||||
135,浪潮,2.1.3.4,应用管理服务,3
|
33,蓝谷信息,2.1.2.2,业务流程模型,30
|
||||||
12,大唐软件,1.2.1,网络互联,3
|
144,树根互联,2.1.2.2,业务流程模型,30
|
||||||
135,浪潮,2.1.3.3,工业引擎服务,3
|
125,华数机器人,1.2.3,数据互通,30
|
||||||
88,HPE,1.1.3,工业服务器,3
|
165,智能云科,2.1.2.3,研发仿真模型,30
|
||||||
89,Rockwell,1.1.2,工业控制器,3
|
47,首自信,2.1.1.4,组态建模工具,30
|
||||||
9,北京航天测控,1.3.3.6,运维保障系统MRO,3
|
47,首自信,2.1.1.1,算法建模工具,29
|
||||||
135,浪潮,1.1.3,工业服务器,3
|
78,OutSystems,2.1.1.4,组态建模工具,29
|
||||||
90,Mentor Graphics,1.3.1.7,电子设计自动化EDA,3
|
13,东方国信,2.3.3,协议转换,29
|
||||||
131,九物互联,2.1.1.4,组态建模工具,3
|
6,安世亚太,2.1.2.2,业务流程模型,29
|
||||||
13,东方国信,1.2.2,标识解析,3
|
128,华伍股份,1.1.2,工业控制器,29
|
||||||
101,Analog Devices,1.1.1,工业计算芯片,3
|
49,数码大方,1.3.1.1,计算机辅助设计CAD,29
|
||||||
127,华为海思,1.1.3,工业服务器,3
|
68,中望软件,1.3.1.2,计算机辅助工程CAE,29
|
||||||
153,武汉开目,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
22,航天云网,2.3.3,协议转换,29
|
||||||
79,PTC,2.3.2,边缘数据处理,3
|
14,东华软件,1.3.3.4,可编程逻揖控制系统PLC,29
|
||||||
161,研华科技,2.3.1,工业数据接入,3
|
168,中控技术,2.3.2,边缘数据处理,28
|
||||||
168,中控技术,1.3.3.2,分布式控制系统DCS,3
|
121,广州智臣,1.4.2.4,安全隔离与信息交换系统,28
|
||||||
22,航天云网,2.1.3.3,工业引擎服务,3
|
62,云道智造,1.3.1.2,计算机辅助工程CAE,28
|
||||||
72,ANSYS,1.3.1.2,计算机辅助工程CAE,3
|
96,Cisco,1.2.3,数据互通,28
|
||||||
22,航天云网,1.2.2,标识解析,3
|
33,蓝谷信息,2.1.2.3,研发仿真模型,28
|
||||||
20,海基科技,1.3.1.2,计算机辅助工程CAE,3
|
123,海得控制,1.1.2,工业控制器,28
|
||||||
119,广联达,1.3.1.1,计算机辅助设计CAD,3
|
32,兰光创新,1.2.3,数据互通,28
|
||||||
168,中控技术,2.3.1,工业数据接入,3
|
17,国保金泰,1.4.2.4,安全隔离与信息交换系统,28
|
||||||
79,PTC,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
51,天地和兴,1.4.2.1,工控安全监测与审计,28
|
||||||
165,智能云科,2.1.2.1,数据算法模型,3
|
6,安世亚太,2.1.2.1,数据算法模型,28
|
||||||
79,PTC,1.3.1.6,产品生命周期管理PLM,3
|
66,中国联通,1.2.1,网络互联,28
|
||||||
79,PTC,1.3.1.1,计算机辅助设计CAD,3
|
161,研华科技,2.3.2,边缘数据处理,28
|
||||||
166,中国电子科技网络信息安全,1.2.3,数据互通,3
|
19,国泰网信,1.4.2.1,工控安全监测与审计,28
|
||||||
165,智能云科,2.1.2.4,行业机理模型,3
|
23,和利时,2.3.3,协议转换,28
|
||||||
58,用友,1.3.1.6,产品生命周期管理PLM,2
|
149,天泽智云,2.1.2.2,业务流程模型,27
|
||||||
117,格创东智,2.1.1.3,流程开发工具,2
|
79,PTC,2.3.3,协议转换,27
|
||||||
70,ABB,1.3.3.2,分布式控制系统DCS,2
|
78,OutSystems,2.1.1.1,算法建模工具,27
|
||||||
10,北京英贝思,1.3.3.5,企业资产管理系统EAM,2
|
126,华为,2.1.1.5,数字孪生建模工具,27
|
||||||
102,Amazon AWS,2.1.4,工业大数据,2
|
165,智能云科,2.1.2.4,行业机理模型,27
|
||||||
99,Siemens,1.1.2,工业控制器,2
|
132,科远智慧,1.3.3.2,分布式控制系统DCS,27
|
||||||
74,HoneyWell,1.3.3.2,分布式控制系统DCS,2
|
135,浪潮,1.1.3,工业服务器,27
|
||||||
77,Oracle,1.3.3.6,运维保障系统MRO,2
|
22,航天云网,2.1.1.1,算法建模工具,27
|
||||||
77,Oracle,1.3.4,企业运营管理,2
|
26,寄云科技,2.1.3.6,微服务,27
|
||||||
49,数码大方,2.1.2.4,行业机理模型,2
|
23,和利时,1.3.3.4,可编程逻揖控制系统PLC,27
|
||||||
50,索为系统,1.3.1.5,产品数据管理PDM,2
|
33,蓝谷信息,2.1.2.4,行业机理模型,27
|
||||||
89,Rockwell,1.2.1,网络互联,2
|
9,北京航天测控,1.3.3.6,运维保障系统MRO,27
|
||||||
58,用友,1.2.2,标识解析,2
|
12,大唐软件,1.2.1,网络互联,27
|
||||||
78,OutSystems,2.1.1.1,算法建模工具,2
|
83,Emerson,1.3.3.2,分布式控制系统DCS,27
|
||||||
56,芯愿景,1.3.1.7,电子设计自动化EDA,2
|
47,首自信,2.1.2.1,数据算法模型,26
|
||||||
111,鼎捷软件,1.3.4.1,企业资源计划ERP,2
|
16,东土科技,1.1.3,工业服务器,26
|
||||||
57,亚控科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
82,Uptake,2.1.2.4,行业机理模型,26
|
||||||
78,OutSystems,2.1.1.3,流程开发工具,2
|
16,东土科技,2.3.1,工业数据接入,26
|
||||||
61,元年科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
53,天融信,1.4.1.5,统一威胁管理系统,26
|
||||||
83,Emerson,1.3.3.2,分布式控制系统DCS,2
|
78,OutSystems,2.1.1.2,低代码开发工具,26
|
||||||
82,Uptake,2.1.2.3,研发仿真模型,2
|
95,Schneider,1.2.3,数据互通,26
|
||||||
60,宇动源,2.1.1.5,数字孪生建模工具,2
|
16,东土科技,2.3.2,边缘数据处理,26
|
||||||
60,宇动源,2.1.1.4,组态建模工具,2
|
49,数码大方,2.1.2.1,数据算法模型,26
|
||||||
62,云道智造,2.1.2.1,数据算法模型,2
|
16,东土科技,2.3.3,协议转换,26
|
||||||
33,蓝谷信息,2.1.2.3,研发仿真模型,2
|
168,中控技术,1.3.3.4,可编程逻揖控制系统PLC,26
|
||||||
48,曙光信息,1.2.2,标识解析,2
|
22,航天云网,1.2.2,标识解析,26
|
||||||
22,航天云网,1.3.3.6,运维保障系统MRO,2
|
165,智能云科,2.1.2.2,业务流程模型,26
|
||||||
26,寄云科技,2.1.3.2,平台基础服务,2
|
38,牛刀,2.1.1.1,算法建模工具,26
|
||||||
144,树根互联,2.1.2.2,业务流程模型,2
|
149,天泽智云,2.1.2.4,行业机理模型,26
|
||||||
25,华大九天,1.3.1.7,电子设计自动化EDA,2
|
22,航天云网,2.1.1.4,组态建模工具,26
|
||||||
23,和利时,1.3.3.3,数据采集与监视控制系统SCADA,2
|
57,亚控科技,1.3.3.3,数据采集与监视控制系统SCADA,26
|
||||||
138,启明信息,1.3.1.5,产品数据管理PDM,2
|
33,蓝谷信息,2.1.2.1,数据算法模型,26
|
||||||
23,和利时,1.3.3.1,制造执行系统MES,2
|
82,Uptake,2.1.2.3,研发仿真模型,26
|
||||||
22,航天云网,2.3.2,边缘数据处理,2
|
6,安世亚太,2.1.2.3,研发仿真模型,25
|
||||||
22,航天云网,2.1.3.5,容器服务,2
|
82,Uptake,2.1.2.1,数据算法模型,25
|
||||||
14,东华软件,1.3.3.4,可编程逻揖控制系统PLC,2
|
22,航天云网,2.1.1.3,流程开发工具,25
|
||||||
22,航天云网,2.1.3.1,物联网服务,2
|
53,天融信,1.4.5.3,数据审计系统,25
|
||||||
22,航天云网,2.1.1.5,数字孪生建模工具,2
|
129,华中数控,1.1.2,工业控制器,25
|
||||||
22,航天云网,2.1.1.3,流程开发工具,2
|
143,沈阳自动化研究所,2.1.1.1,算法建模工具,25
|
||||||
22,航天云网,2.1.1.2,低代码开发工具,2
|
23,和利时,2.3.1,工业数据接入,25
|
||||||
22,航天云网,2.1.1.1,算法建模工具,2
|
57,亚控科技,2.3.3,协议转换,25
|
||||||
141,上海新华控制,1.3.3.2,分布式控制系统DCS,2
|
65,中国电信,1.2.1,网络互联,25
|
||||||
26,寄云科技,2.1.3.5,容器服务,2
|
41,启明星辰,1.4.1.2,下一代防火墙,25
|
||||||
2,706所,1.1.3,工业服务器,2
|
49,数码大方,2.1.2.2,业务流程模型,25
|
||||||
124,海尔,1.2.1,网络互联,2
|
140,山石网科,1.4.1.4,入侵检测系统,25
|
||||||
168,中控技术,1.3.3.4,可编程逻揖控制系统PLC,2
|
41,启明星辰,1.4.1.5,统一威胁管理系统,25
|
||||||
143,沈阳自动化研究所,2.1.1.2,低代码开发工具,2
|
57,亚控科技,2.3.2,边缘数据处理,25
|
||||||
168,中控技术,1.1.2,工业控制器,2
|
111,鼎捷软件,1.3.4.1,企业资源计划ERP,25
|
||||||
143,沈阳自动化研究所,2.1.1.3,流程开发工具,2
|
49,数码大方,2.1.2.4,行业机理模型,24
|
||||||
164,震坤行,1.3.3.6,运维保障系统MRO,2
|
22,航天云网,2.1.1.2,低代码开发工具,24
|
||||||
163,优也科技,2.1.4.2.2,数据安全管理,2
|
62,云道智造,2.1.2.1,数据算法模型,24
|
||||||
143,沈阳自动化研究所,2.1.1.4,组态建模工具,2
|
7,百望,2.2,IaaS,24
|
||||||
156,芯禾科技,1.3.1.7,电子设计自动化EDA,2
|
168,中控技术,1.1.2,工业控制器,24
|
||||||
143,沈阳自动化研究所,2.1.1.5,数字孪生建模工具,2
|
18,国能智深,1.3.3.2,分布式控制系统DCS,24
|
||||||
144,树根互联,2.1.2.1,数据算法模型,2
|
143,沈阳自动化研究所,2.1.1.3,流程开发工具,24
|
||||||
15,东软集团,1.3.3.5,企业资产管理系统EAM,2
|
53,天融信,1.4.1.4,入侵检测系统,24
|
||||||
149,天泽智云,2.1.2.1,数据算法模型,2
|
149,天泽智云,2.1.2.3,研发仿真模型,24
|
||||||
26,寄云科技,2.1.3.4,应用管理服务,2
|
45,石化盈科,1.3.4.1,企业资源计划ERP,24
|
||||||
144,树根互联,2.1.2.3,研发仿真模型,2
|
136,美的,1.2.1,网络互联,24
|
||||||
26,寄云科技,2.1.3.7,制造类API,2
|
143,沈阳自动化研究所,2.1.1.2,低代码开发工具,24
|
||||||
135,浪潮,2.1.3.1,物联网服务,2
|
141,上海新华控制,1.3.3.2,分布式控制系统DCS,24
|
||||||
117,格创东智,2.1.1.5,数字孪生建模工具,2
|
135,浪潮,1.3.4.1,企业资源计划ERP,24
|
||||||
134,朗坤智慧,1.3.3.5,企业资产管理系统EAM,2
|
22,航天云网,2.3.1,工业数据接入,24
|
||||||
13,东方国信,2.3.3,协议转换,2
|
115,富士康,1.1.3,工业服务器,24
|
||||||
38,牛刀,2.1.1.2,低代码开发工具,2
|
38,牛刀,2.1.1.3,流程开发工具,24
|
||||||
38,牛刀,2.1.1.1,算法建模工具,2
|
23,和利时,1.3.3.3,数据采集与监视控制系统SCADA,24
|
||||||
13,东方国信,2.1.4.1.4,时序数据库,2
|
62,云道智造,2.1.2.4,行业机理模型,23
|
||||||
34,力控科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
62,云道智造,2.1.2.3,研发仿真模型,23
|
||||||
135,浪潮,2.1.3.2,平台基础服务,2
|
144,树根互联,2.1.2.3,研发仿真模型,23
|
||||||
128,华伍股份,1.1.2,工业控制器,2
|
5,安华金和,1.4.5.3,数据审计系统,23
|
||||||
47,首自信,2.1.2.2,业务流程模型,2
|
89,Rockwell,1.3.3.1,制造执行系统MES,23
|
||||||
135,浪潮,2.1.3.5,容器服务,2
|
58,用友,1.3.4.1,企业资源计划ERP,23
|
||||||
135,浪潮,2.1.3.6,微服务,2
|
60,宇动源,2.1.1.5,数字孪生建模工具,23
|
||||||
131,九物互联,2.1.1.1,算法建模工具,2
|
111,鼎捷软件,1.3.3.1,制造执行系统MES,23
|
||||||
99,Siemens,1.2.1,网络互联,1
|
82,Uptake,2.1.2.2,业务流程模型,23
|
||||||
13,东方国信,2.1.4.1.2,分布式数据库,1
|
60,宇动源,2.1.1.1,算法建模工具,23
|
||||||
131,九物互联,2.1.1.3,流程开发工具,1
|
165,智能云科,2.1.2.1,数据算法模型,23
|
||||||
111,鼎捷软件,1.3.3.1,制造执行系统MES,1
|
22,航天云网,2.1.4.1.3,实时数据库,22
|
||||||
129,华中数控,1.2.3,数据互通,1
|
143,沈阳自动化研究所,2.1.1.5,数字孪生建模工具,22
|
||||||
13,东方国信,2.1.4.2.1,数据质量管理,1
|
55,威努特,1.4.1.2,下一代防火墙,22
|
||||||
126,华为,2.1.1.5,数字孪生建模工具,1
|
60,宇动源,2.1.1.2,低代码开发工具,22
|
||||||
130,金蝶,1.3.4.1,企业资源计划ERP,1
|
144,树根互联,2.1.2.4,行业机理模型,22
|
||||||
96,Cisco,1.2.3,数据互通,1
|
169,中芯国际,1.1.1,工业计算芯片,22
|
||||||
91,Moxa,1.2.1,网络互联,1
|
53,天融信,1.4.3.3,APT检测,22
|
||||||
132,科远智慧,1.3.3.2,分布式控制系统DCS,1
|
129,华中数控,1.2.3,数据互通,22
|
||||||
133,蓝盾股份,1.4.4.1,身份鉴别与访问控制,1
|
89,Rockwell,1.1.2,工业控制器,22
|
||||||
92,Omron,1.3.3.4,可编程逻揖控制系统PLC,1
|
78,OutSystems,2.1.1.3,流程开发工具,22
|
||||||
108,百度,2.2,IaaS,1
|
3,艾克斯特,1.3.4.1,企业资源计划ERP,22
|
||||||
14,东华软件,1.3.4.3,人力资源管理HRM,1
|
131,九物互联,2.1.1.3,流程开发工具,22
|
||||||
125,华数机器人,1.2.3,数据互通,1
|
140,山石网科,1.4.5.3,数据审计系统,22
|
||||||
139,容知日新,1.3.3.7,故障预测与健康管理PHM,1
|
38,牛刀,2.1.1.4,组态建模工具,22
|
||||||
89,Rockwell,1.3.3.1,制造执行系统MES,1
|
99,Siemens,1.1.2,工业控制器,22
|
||||||
135,浪潮,1.3.4.1,企业资源计划ERP,1
|
37,绿盟,1.4.1.2,下一代防火墙,21
|
||||||
137,美林数据,2.1.4.2.1,数据质量管理,1
|
103,STMicroelectronics ,1.1.1,工业计算芯片,21
|
||||||
137,美林数据,2.1.4.1.3,实时数据库,1
|
62,云道智造,2.1.2.2,业务流程模型,21
|
||||||
84,Bosch,2.1.4,工业大数据,1
|
149,天泽智云,2.1.2.1,数据算法模型,21
|
||||||
135,浪潮,2.2,IaaS,1
|
36,龙芯中科,1.1.1,工业计算芯片,21
|
||||||
109,宝信软件,1.3.3.1,制造执行系统MES,1
|
47,首自信,2.1.1.3,流程开发工具,21
|
||||||
18,国能智深,1.3.3.2,分布式控制系统DCS,1
|
45,石化盈科,2.1.4.1.2,分布式数据库,21
|
||||||
154,西格数据,2.1.4.1.2,分布式数据库,1
|
44,圣邦微电子,1.1.1,工业计算芯片,21
|
||||||
45,石化盈科,1.3.4.1,企业资源计划ERP,1
|
167,中环股份,1.1.1,工业计算芯片,21
|
||||||
115,富士康,2.1.4,工业大数据,1
|
40,奇安信,1.4.3.3,APT检测,21
|
||||||
38,牛刀,2.1.1.3,流程开发工具,1
|
130,金蝶,1.3.4.1,企业资源计划ERP,21
|
||||||
38,牛刀,2.1.1.4,组态建模工具,1
|
49,数码大方,1.3.3.1,制造执行系统MES,21
|
||||||
117,格创东智,2.1.4.2.1,数据质量管理,1
|
60,宇动源,2.1.1.3,流程开发工具,20
|
||||||
117,格创东智,2.1.4.1.1,关系型数据库,1
|
91,Moxa,1.2.1,网络互联,20
|
||||||
42,山大华天,1.3.1.3,计算机辅助制造CAM,1
|
69,紫光集团,1.1.1,工业计算芯片,20
|
||||||
43,神舟软件,1.3.1.5,产品数据管理PDM,1
|
70,ABB,1.3.3.2,分布式控制系统DCS,20
|
||||||
45,石化盈科,1.3.3.1,制造执行系统MES,1
|
22,航天云网,2.1.1.5,数字孪生建模工具,20
|
||||||
45,石化盈科,2.1.4.1.2,分布式数据库,1
|
38,牛刀,2.1.1.2,低代码开发工具,20
|
||||||
31,昆仑数据,2.1.4.2.1,数据质量管理,1
|
55,威努特,1.4.2.1,工控安全监测与审计,20
|
||||||
45,石化盈科,2.1.4.1.3,实时数据库,1
|
28,金山云,2.2,IaaS,20
|
||||||
45,石化盈科,2.1.4.1.4,时序数据库,1
|
31,昆仑数据,1.3.3.3,数据采集与监视控制系统SCADA,20
|
||||||
45,石化盈科,2.1.4.2.1,数据质量管理,1
|
22,航天云网,2.1.4.2.1,数据质量管理,20
|
||||||
45,石化盈科,2.1.4.2.2,数据安全管理,1
|
38,牛刀,2.1.1.5,数字孪生建模工具,20
|
||||||
49,数码大方,2.1.2.3,研发仿真模型,1
|
23,和利时,1.3.3.1,制造执行系统MES,19
|
||||||
47,首自信,2.1.1.1,算法建模工具,1
|
45,石化盈科,2.1.4.1.4,时序数据库,19
|
||||||
47,首自信,2.1.1.3,流程开发工具,1
|
89,Rockwell,1.2.1,网络互联,19
|
||||||
47,首自信,2.1.1.4,组态建模工具,1
|
37,绿盟,1.4.1.4,入侵检测系统,19
|
||||||
33,蓝谷信息,2.1.2.1,数据算法模型,1
|
113,飞腾信息,1.1.1,工业计算芯片,19
|
||||||
31,昆仑数据,2.1.4.1.3,实时数据库,1
|
13,东方国信,2.1.4.1.4,时序数据库,19
|
||||||
154,西格数据,2.1.4.2.2,数据安全管理,1
|
23,和利时,1.1.2,工业控制器,19
|
||||||
70,ABB,1.3.3.4,可编程逻揖控制系统PLC,1
|
60,宇动源,2.1.1.4,组态建模工具,19
|
||||||
163,优也科技,2.1.4.1.1,关系型数据库,1
|
163,优也科技,2.1.4.2.1,数据质量管理,19
|
||||||
163,优也科技,2.1.4.1.4,时序数据库,1
|
117,格创东智,2.1.1.2,低代码开发工具,19
|
||||||
165,智能云科,2.1.2.3,研发仿真模型,1
|
117,格创东智,2.1.1.3,流程开发工具,19
|
||||||
168,中控技术,1.3.3.1,制造执行系统MES,1
|
87,Texas Instruments,1.1.1,工业计算芯片,18
|
||||||
47,首自信,2.1.2.3,研发仿真模型,1
|
131,九物互联,2.1.1.1,算法建模工具,18
|
||||||
21,Hexagon,1.3.1.3,计算机辅助制造CAM,1
|
137,美林数据,2.1.4.2.2,数据安全管理,18
|
||||||
22,航天云网,2.1.1.4,组态建模工具,1
|
131,九物互联,2.1.1.4,组态建模工具,18
|
||||||
22,航天云网,2.1.3.2,平台基础服务,1
|
154,西格数据,2.1.4.1.2,分布式数据库,18
|
||||||
23,和利时,1.3.3.2,分布式控制系统DCS,1
|
63,长扬科技,1.4.1.1,工业防火墙,18
|
||||||
31,昆仑数据,2.1.4.1.1,关系型数据库,1
|
104,Infineon,1.1.1,工业计算芯片,18
|
||||||
66,中国联通,1.2.1,网络互联,1
|
101,Analog Devices,1.1.1,工业计算芯片,18
|
||||||
23,和利时,1.3.3.4,可编程逻揖控制系统PLC,1
|
22,航天云网,1.3.3.6,运维保障系统MRO,18
|
||||||
118,工邦邦,1.3.3.6,运维保障系统MRO,1
|
45,石化盈科,1.3.3.1,制造执行系统MES,18
|
||||||
1,51WORLD,2.1.1.5,数字孪生建模工具,1
|
168,中控技术,1.3.3.1,制造执行系统MES,17
|
||||||
62,云道智造,2.1.2.3,研发仿真模型,1
|
24,华大电子,1.1.1,工业计算芯片,17
|
||||||
117,格创东智,2.1.4.2.2,数据安全管理,1
|
13,东方国信,2.1.4.2.2,数据安全管理,17
|
||||||
3,艾克斯特,1.3.4.1,企业资源计划ERP,1
|
31,昆仑数据,2.1.4.2.1,数据质量管理,17
|
||||||
60,宇动源,2.1.1.3,流程开发工具,1
|
13,东方国信,2.1.4.1.2,分布式数据库,17
|
||||||
126,华为,2.2,IaaS,1
|
96,Cisco,1.2.1,网络互联,17
|
||||||
|
22,航天云网,2.1.4.2.2,数据安全管理,17
|
||||||
|
22,航天云网,2.1.4.1.2,分布式数据库,17
|
||||||
|
117,格创东智,2.1.1.1,算法建模工具,17
|
||||||
|
163,优也科技,2.1.4.1.4,时序数据库,17
|
||||||
|
140,山石网科,1.4.1.5,统一威胁管理系统,17
|
||||||
|
154,西格数据,2.1.4.1.4,时序数据库,17
|
||||||
|
55,威努特,1.4.1.1,工业防火墙,17
|
||||||
|
74,HoneyWell,1.3.3.2,分布式控制系统DCS,17
|
||||||
|
117,格创东智,2.1.1.5,数字孪生建模工具,17
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,17
|
||||||
|
137,美林数据,2.1.4.1.4,时序数据库,17
|
||||||
|
163,优也科技,2.1.4.1.1,关系型数据库,16
|
||||||
|
124,海尔,1.2.1,网络互联,16
|
||||||
|
45,石化盈科,2.1.4.1.1,关系型数据库,16
|
||||||
|
117,格创东智,2.1.1.4,组态建模工具,16
|
||||||
|
22,航天云网,2.1.4.1.1,关系型数据库,16
|
||||||
|
31,昆仑数据,2.1.4.1.1,关系型数据库,16
|
||||||
|
137,美林数据,2.1.4.2.1,数据质量管理,16
|
||||||
|
163,优也科技,2.1.4.1.2,分布式数据库,15
|
||||||
|
137,美林数据,2.1.4.1.2,分布式数据库,15
|
||||||
|
55,威努特,1.4.1.3,防毒墙,15
|
||||||
|
117,格创东智,2.1.4.1.1,关系型数据库,15
|
||||||
|
131,九物互联,2.1.1.2,低代码开发工具,15
|
||||||
|
31,昆仑数据,2.1.4.1.3,实时数据库,15
|
||||||
|
154,西格数据,2.1.4.2.1,数据质量管理,15
|
||||||
|
127,华为海思,1.1.1,工业计算芯片,15
|
||||||
|
154,西格数据,2.1.4.2.2,数据安全管理,15
|
||||||
|
137,美林数据,2.1.4.1.3,实时数据库,15
|
||||||
|
22,航天云网,1.2.1,网络互联,15
|
||||||
|
45,石化盈科,2.1.4.1.3,实时数据库,14
|
||||||
|
45,石化盈科,2.1.4.2.1,数据质量管理,14
|
||||||
|
40,奇安信,1.4.2.1,工控安全监测与审计,14
|
||||||
|
163,优也科技,2.1.4.2.2,数据安全管理,14
|
||||||
|
133,蓝盾股份,1.4.1.3,防毒墙,14
|
||||||
|
154,西格数据,2.1.4.1.1,关系型数据库,14
|
||||||
|
31,昆仑数据,2.1.4.2.2,数据安全管理,13
|
||||||
|
168,中控技术,1.3.3.2,分布式控制系统DCS,13
|
||||||
|
131,九物互联,2.1.1.5,数字孪生建模工具,13
|
||||||
|
54,网御星云,1.4.2.4,安全隔离与信息交换系统,13
|
||||||
|
154,西格数据,2.1.4.1.3,实时数据库,13
|
||||||
|
13,东方国信,2.1.4.1.3,实时数据库,12
|
||||||
|
117,格创东智,2.1.4.1.3,实时数据库,12
|
||||||
|
13,东方国信,2.1.4.1.1,关系型数据库,12
|
||||||
|
126,华为,2.2,IaaS,12
|
||||||
|
117,格创东智,2.1.4.2.2,数据安全管理,12
|
||||||
|
137,美林数据,2.1.4.1.1,关系型数据库,12
|
||||||
|
31,昆仑数据,2.1.4.1.2,分布式数据库,11
|
||||||
|
117,格创东智,2.1.4.2.1,数据质量管理,11
|
||||||
|
45,石化盈科,2.1.4.2.2,数据安全管理,11
|
||||||
|
53,天融信,1.4.1.3,防毒墙,11
|
||||||
|
117,格创东智,2.1.4.1.2,分布式数据库,11
|
||||||
|
78,OutSystems,2.1.1.5,数字孪生建模工具,11
|
||||||
|
117,格创东智,2.1.4.1.4,时序数据库,11
|
||||||
|
163,优也科技,2.1.4.1.3,实时数据库,11
|
||||||
|
31,昆仑数据,2.1.4.1.4,时序数据库,11
|
||||||
|
142,深信服,1.4.1.1,工业防火墙,10
|
||||||
|
106,阿里巴巴,2.2,IaaS,10
|
||||||
|
13,东方国信,2.1.4.2.1,数据质量管理,10
|
||||||
|
54,网御星云,1.4.1.3,防毒墙,10
|
||||||
|
148,腾讯,2.2,IaaS,10
|
||||||
|
23,和利时,1.3.3.2,分布式控制系统DCS,10
|
||||||
|
22,航天云网,2.1.4.1.4,时序数据库,9
|
||||||
|
99,Siemens,1.2.1,网络互联,9
|
||||||
|
53,天融信,1.4.2.4,安全隔离与信息交换系统,8
|
||||||
|
63,长扬科技,1.4.2.4,安全隔离与信息交换系统,8
|
||||||
|
135,浪潮,2.2,IaaS,7
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,7
|
||||||
|
108,百度,2.2,IaaS,7
|
||||||
|
140,山石网科,1.4.1.1,工业防火墙,6
|
||||||
|
|
|
|
@ -1,82 +1,108 @@
|
||||||
id_product,Name,count
|
id_product,Name,count
|
||||||
1.4,工业互联网安全,385
|
2.1.3,工业物联网,2810
|
||||||
2.1.3,工业物联网,184
|
1.3.1,设计研发,2246
|
||||||
1.4.5,数据安全,150
|
1,供给,1525
|
||||||
1.4.3,网络安全,150
|
1.3.3,生产制造,1296
|
||||||
1.4.2,控制安全,150
|
2.1.2,工业模型库,1269
|
||||||
1,供给,125
|
2.1.1,开发工具,1159
|
||||||
1.3,工业软件,119
|
2.3,边缘层,1073
|
||||||
1.3.1,设计研发,119
|
1.4,工业互联网安全,1012
|
||||||
1.1,工业自动化,114
|
1.1,工业自动化,904
|
||||||
2.1.2,工业模型库,103
|
1.3,工业软件,886
|
||||||
2.3,边缘层,102
|
1.2,工业互联网网络,751
|
||||||
2,工业互联网平台,83
|
1.4.4,平台安全,709
|
||||||
2.1.1,开发工具,82
|
1.4.5,数据安全,640
|
||||||
1.4.4,平台安全,77
|
2.1.4.1,工业大数据存储,595
|
||||||
1.3.2,采购供应,76
|
1.3.4,企业运营管理,592
|
||||||
1.1.1,工业计算芯片,67
|
1.4.2,控制安全,529
|
||||||
1.3.3,生产制造,60
|
2,工业互联网平台,436
|
||||||
2.1,PaaS,50
|
1.4.3,网络安全,430
|
||||||
1.3.5,仓储物流,50
|
1.4.1,设备安全,418
|
||||||
|
2.1.4,工业大数据,372
|
||||||
|
2.1.4.2,工业大数据管理,342
|
||||||
|
2.1,PaaS,323
|
||||||
|
1.1.1,工业计算芯片,255
|
||||||
|
2.1.3.6,微服务,249
|
||||||
|
2.1.2.3,研发仿真模型,241
|
||||||
|
2.1.2.2,业务流程模型,241
|
||||||
|
1.3.1.2,计算机辅助工程CAE,241
|
||||||
|
2.1.2.4,行业机理模型,237
|
||||||
|
2.3.1,工业数据接入,237
|
||||||
|
1.3.1.1,计算机辅助设计CAD,236
|
||||||
|
1.1.2,工业控制器,233
|
||||||
|
2.1.2.1,数据算法模型,230
|
||||||
|
2.3.2,边缘数据处理,230
|
||||||
|
2.3.3,协议转换,227
|
||||||
|
2.1.3.2,平台基础服务,212
|
||||||
|
2.1.3.4,应用管理服务,211
|
||||||
|
1.1.3,工业服务器,211
|
||||||
|
2.1.3.5,容器服务,211
|
||||||
|
2.1.3.3,工业引擎服务,207
|
||||||
|
1.3.1.4,计算机辅助工艺过程设计CAPP,207
|
||||||
|
2.1.3.7,制造类API,206
|
||||||
|
2.1.3.1,物联网服务,203
|
||||||
|
1.3.1.7,电子设计自动化EDA,201
|
||||||
|
1.2.3,数据互通,201
|
||||||
|
1.3.1.6,产品生命周期管理PLM,200
|
||||||
|
1.2.1,网络互联,200
|
||||||
|
2.1.1.1,算法建模工具,192
|
||||||
|
2.1.1.4,组态建模工具,191
|
||||||
|
2.1.1.5,数字孪生建模工具,184
|
||||||
|
2.1.1.2,低代码开发工具,184
|
||||||
|
2.1.1.3,流程开发工具,177
|
||||||
|
1.3.2,采购供应,176
|
||||||
|
1.3.1.5,产品数据管理PDM,166
|
||||||
|
1.3.1.3,计算机辅助制造CAM,166
|
||||||
|
1.2.2,标识解析,164
|
||||||
|
1.3.3.2,分布式控制系统DCS,162
|
||||||
|
1.3.3.1,制造执行系统MES,155
|
||||||
|
1.3.3.4,可编程逻揖控制系统PLC,147
|
||||||
|
1.3.3.6,运维保障系统MRO,143
|
||||||
|
1.3.4.1,企业资源计划ERP,139
|
||||||
|
1.3.3.5,企业资产管理系统EAM,138
|
||||||
|
1.3.3.3,数据采集与监视控制系统SCADA,134
|
||||||
|
2.1.4.1.2,分布式数据库,125
|
||||||
|
2.1.4.2.1,数据质量管理,122
|
||||||
|
1.3.4.3,人力资源管理HRM,121
|
||||||
|
1.3.4.2,客户关系管理CRM,121
|
||||||
|
2.1.4.1.4,时序数据库,120
|
||||||
|
1.3.5,仓储物流,120
|
||||||
|
1.4.4.1,身份鉴别与访问控制,119
|
||||||
|
2.1.4.2.2,数据安全管理,117
|
||||||
|
2.1.4.1.1,关系型数据库,117
|
||||||
|
1.3.3.7,故障预测与健康管理PHM,116
|
||||||
|
2.1.4.1.3,实时数据库,114
|
||||||
|
1.4.2.1,工控安全监测与审计,90
|
||||||
|
2.2,IaaS,90
|
||||||
|
1.4.4.3,接入认证,90
|
||||||
|
1.4.4.4,工业应用行为监控,90
|
||||||
|
1.4.4.2,密钥管理,90
|
||||||
|
1.4.2.4,安全隔离与信息交换系统,85
|
||||||
|
1.4.1.3,防毒墙,83
|
||||||
|
1.4.1.1,工业防火墙,81
|
||||||
|
1.4.3.3,APT检测,76
|
||||||
|
1.4.5.9,数据防火墙,70
|
||||||
|
1.4.5.7,数据恢复,70
|
||||||
|
1.4.5.6,数据容灾备份,70
|
||||||
|
1.4.5.5,敏感数据发现与监控,70
|
||||||
|
1.4.5.4,数据脱敏,70
|
||||||
|
1.4.5.3,数据审计系统,70
|
||||||
|
1.4.5.2,数据防泄漏系统,70
|
||||||
|
1.3.5.1,仓储物流管理WMS,70
|
||||||
|
1.4.3.4,攻击溯源,68
|
||||||
|
1.4.3.5,负载均衡,68
|
||||||
|
1.4.3.1,网络漏洞扫描和补丁管理,68
|
||||||
|
1.4.2.6,隐私计算,68
|
||||||
|
1.4.2.5,安全日志与审计,68
|
||||||
|
1.4.2.2,工控主机卫士,68
|
||||||
|
1.4.1.5,统一威胁管理系统,68
|
||||||
|
1.4.1.4,入侵检测系统,68
|
||||||
|
1.4.1.2,下一代防火墙,68
|
||||||
1.3.2.1,供应链管理SCM,50
|
1.3.2.1,供应链管理SCM,50
|
||||||
1.4.5.8,数据加密,50
|
|
||||||
1.4.5.1,恶意代码检测系统,50
|
1.4.5.1,恶意代码检测系统,50
|
||||||
1.4.4.5,安全态势感知,50
|
1.4.4.5,安全态势感知,50
|
||||||
1.4.3.6,沙箱类设备,50
|
1.4.3.6,沙箱类设备,50
|
||||||
1.4.3.2,流量检测,50
|
1.4.3.2,流量检测,50
|
||||||
1.4.2.7,工控原生安全,50
|
1.4.2.7,工控原生安全,50
|
||||||
1.4.2.3,工控漏洞扫描,50
|
1.4.2.3,工控漏洞扫描,50
|
||||||
1.4.1,设备安全,50
|
1.4.5.8,数据加密,50
|
||||||
1.2,工业互联网网络,43
|
|
||||||
2.3.3,协议转换,37
|
|
||||||
2.3.1,工业数据接入,33
|
|
||||||
2.1.3.6,微服务,33
|
|
||||||
2.3.2,边缘数据处理,30
|
|
||||||
2.1.2.4,行业机理模型,30
|
|
||||||
2.1.3.4,应用管理服务,29
|
|
||||||
1.3.1.1,计算机辅助设计CAD,28
|
|
||||||
2.1.2.2,业务流程模型,28
|
|
||||||
2.1.2.1,数据算法模型,27
|
|
||||||
2.1.3.7,制造类API,27
|
|
||||||
1.3.1.2,计算机辅助工程CAE,26
|
|
||||||
2.1.3.1,物联网服务,25
|
|
||||||
1.1.2,工业控制器,24
|
|
||||||
2.1.3.5,容器服务,24
|
|
||||||
2.1.3.3,工业引擎服务,23
|
|
||||||
2.1.1.2,低代码开发工具,23
|
|
||||||
1.1.3,工业服务器,23
|
|
||||||
2.1.3.2,平台基础服务,21
|
|
||||||
1.3.1.4,计算机辅助工艺过程设计CAPP,20
|
|
||||||
2.1.2.3,研发仿真模型,18
|
|
||||||
2.1.1.5,数字孪生建模工具,18
|
|
||||||
1.3.1.6,产品生命周期管理PLM,18
|
|
||||||
1.2.3,数据互通,17
|
|
||||||
2.1.1.1,算法建模工具,15
|
|
||||||
2.1.1.4,组态建模工具,14
|
|
||||||
2.1.4.1,工业大数据存储,14
|
|
||||||
1.3.3.2,分布式控制系统DCS,14
|
|
||||||
1.2.2,标识解析,13
|
|
||||||
1.2.1,网络互联,13
|
|
||||||
2.1.4.2,工业大数据管理,12
|
|
||||||
1.3.1.7,电子设计自动化EDA,12
|
|
||||||
2.1.1.3,流程开发工具,12
|
|
||||||
1.3.3.3,数据采集与监视控制系统SCADA,11
|
|
||||||
1.3.3.1,制造执行系统MES,10
|
|
||||||
1.3.3.6,运维保障系统MRO,10
|
|
||||||
1.3.4,企业运营管理,8
|
|
||||||
1.3.3.4,可编程逻揖控制系统PLC,7
|
|
||||||
1.3.3.5,企业资产管理系统EAM,6
|
|
||||||
1.3.4.1,企业资源计划ERP,6
|
|
||||||
2.1.4.2.1,数据质量管理,5
|
|
||||||
2.1.4.2.2,数据安全管理,5
|
|
||||||
1.3.1.5,产品数据管理PDM,5
|
|
||||||
2.1.4,工业大数据,4
|
|
||||||
2.1.4.1.4,时序数据库,4
|
|
||||||
2.1.4.1.1,关系型数据库,3
|
|
||||||
2.1.4.1.2,分布式数据库,3
|
|
||||||
2.1.4.1.3,实时数据库,3
|
|
||||||
2.2,IaaS,3
|
|
||||||
1.3.1.3,计算机辅助制造CAM,2
|
|
||||||
1.3.3.7,故障预测与健康管理PHM,1
|
|
||||||
1.4.4.1,身份鉴别与访问控制,1
|
|
||||||
1.3.4.3,人力资源管理HRM,1
|
|
||||||
|
|
|
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|
@ -0,0 +1,700 @@
|
||||||
|
up_id_firm,up_name_firm,up_id_product,up_name_product,down_id_firm,down_name_firm,down_id_product,down_name_product,count
|
||||||
|
126,华为,1.4,工业互联网安全,170,Pseudo1,1,供给,118
|
||||||
|
142,深信服,1.4.3,网络安全,126,华为,1.4,工业互联网安全,96
|
||||||
|
41,启明星辰,1.4.5,数据安全,126,华为,1.4,工业互联网安全,92
|
||||||
|
142,深信服,1.4.2,控制安全,126,华为,1.4,工业互联网安全,92
|
||||||
|
53,天融信,1.4.3.6,沙箱类设备,142,深信服,1.4.3,网络安全,50
|
||||||
|
23,和利时,1.4.2.7,工控原生安全,142,深信服,1.4.2,控制安全,50
|
||||||
|
157,新华三,1.4.1,设备安全,126,华为,1.4,工业互联网安全,50
|
||||||
|
53,天融信,1.4.5.8,数据加密,41,启明星辰,1.4.5,数据安全,50
|
||||||
|
41,启明星辰,1.4.3.2,流量检测,142,深信服,1.4.3,网络安全,50
|
||||||
|
53,天融信,1.4.2.3,工控漏洞扫描,142,深信服,1.4.2,控制安全,50
|
||||||
|
140,山石网科,1.4.5.1,恶意代码检测系统,41,启明星辰,1.4.5,数据安全,50
|
||||||
|
99,Siemens,2.1,PaaS,102,Amazon AWS,2,工业互联网平台,41
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,130,金蝶,1.3.2,采购供应,40
|
||||||
|
130,金蝶,1.3.5,仓储物流,106,阿里巴巴,1.3,工业软件,39
|
||||||
|
63,长扬科技,1.4.4.5,安全态势感知,0,360科技,1.4.4,平台安全,38
|
||||||
|
63,长扬科技,1.4.4.5,安全态势感知,40,奇安信,1.4.4,平台安全,38
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,58,用友,1.3.2,采购供应,36
|
||||||
|
99,Siemens,2.1,PaaS,98,Microsoft Azure,2,工业互联网平台,36
|
||||||
|
130,金蝶,1.3.5,仓储物流,29,京东工业品,1.3,工业软件,33
|
||||||
|
130,金蝶,1.3.2,采购供应,106,阿里巴巴,1.3,工业软件,23
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,106,阿里巴巴,1.3,工业软件,23
|
||||||
|
53,天融信,1.4.3.6,沙箱类设备,126,华为,1.4,工业互联网安全,23
|
||||||
|
41,启明星辰,1.4.3.2,流量检测,126,华为,1.4,工业互联网安全,23
|
||||||
|
58,用友,1.3.2,采购供应,106,阿里巴巴,1.3,工业软件,23
|
||||||
|
53,天融信,1.4.5.8,数据加密,126,华为,1.4,工业互联网安全,21
|
||||||
|
140,山石网科,1.4.5.1,恶意代码检测系统,126,华为,1.4,工业互联网安全,21
|
||||||
|
142,深信服,1.4.3,网络安全,170,Pseudo1,1,供给,21
|
||||||
|
53,天融信,1.4.2.3,工控漏洞扫描,126,华为,1.4,工业互联网安全,21
|
||||||
|
23,和利时,1.4.2.7,工控原生安全,126,华为,1.4,工业互联网安全,21
|
||||||
|
41,启明星辰,1.4.5,数据安全,170,Pseudo1,1,供给,19
|
||||||
|
142,深信服,1.4.2,控制安全,170,Pseudo1,1,供给,19
|
||||||
|
130,金蝶,1.3.2,采购供应,29,京东工业品,1.3,工业软件,14
|
||||||
|
58,用友,1.3.2,采购供应,29,京东工业品,1.3,工业软件,14
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,29,京东工业品,1.3,工业软件,14
|
||||||
|
157,新华三,1.4.1,设备安全,170,Pseudo1,1,供给,9
|
||||||
|
41,启明星辰,1.4.3.2,流量检测,170,Pseudo1,1,供给,6
|
||||||
|
53,天融信,1.4.3.6,沙箱类设备,170,Pseudo1,1,供给,6
|
||||||
|
99,Siemens,2.1,PaaS,170,Pseudo1,1,供给,5
|
||||||
|
53,天融信,1.4.2.3,工控漏洞扫描,170,Pseudo1,1,供给,5
|
||||||
|
40,奇安信,1.4.4,平台安全,126,华为,1.4,工业互联网安全,5
|
||||||
|
98,Microsoft Azure,2,工业互联网平台,170,Pseudo1,1,供给,5
|
||||||
|
63,长扬科技,1.4.4.5,安全态势感知,126,华为,1.4,工业互联网安全,5
|
||||||
|
140,山石网科,1.4.5.1,恶意代码检测系统,170,Pseudo1,1,供给,5
|
||||||
|
23,和利时,1.4.2.7,工控原生安全,170,Pseudo1,1,供给,5
|
||||||
|
53,天融信,1.4.5.8,数据加密,170,Pseudo1,1,供给,5
|
||||||
|
0,360科技,1.4.4,平台安全,126,华为,1.4,工业互联网安全,5
|
||||||
|
102,Amazon AWS,2,工业互联网平台,170,Pseudo1,1,供给,5
|
||||||
|
131,九物互联,2.1.1.2,低代码开发工具,106,阿里巴巴,2.1.1,开发工具,4
|
||||||
|
42,山大华天,1.3.1.1,计算机辅助设计CAD,85,Dassault,1.3.1,设计研发,4
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,74,HoneyWell,2.1.3,工业物联网,4
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,106,阿里巴巴,2.1.3,工业物联网,4
|
||||||
|
78,OutSystems,2.1.1.5,数字孪生建模工具,80,Salesforce,2.1.1,开发工具,3
|
||||||
|
68,中望软件,1.3.1.2,计算机辅助工程CAE,85,Dassault,1.3.1,设计研发,3
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,74,HoneyWell,2.1.3,工业物联网,3
|
||||||
|
13,东方国信,2.1.3.6,微服务,74,HoneyWell,2.1.3,工业物联网,3
|
||||||
|
13,东方国信,2.1.3.7,制造类API,106,阿里巴巴,2.1.3,工业物联网,3
|
||||||
|
13,东方国信,2.1.3.7,制造类API,108,百度,2.1.3,工业物联网,3
|
||||||
|
79,PTC,2.3.3,协议转换,126,华为,2.3,边缘层,3
|
||||||
|
69,紫光集团,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,3
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,73,FANUC,2.1.3,工业物联网,3
|
||||||
|
43,神舟软件,1.3.1.6,产品生命周期管理PLM,85,Dassault,1.3.1,设计研发,3
|
||||||
|
16,东土科技,2.3.3,协议转换,126,华为,2.3,边缘层,3
|
||||||
|
79,PTC,2.1.3.6,微服务,108,百度,2.1.3,工业物联网,3
|
||||||
|
117,格创东智,2.1.1.1,算法建模工具,80,Salesforce,2.1.1,开发工具,3
|
||||||
|
79,PTC,2.1.3.1,物联网服务,74,HoneyWell,2.1.3,工业物联网,3
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,74,HoneyWell,2.1.3,工业物联网,3
|
||||||
|
79,PTC,2.1.3.7,制造类API,148,腾讯,2.1.3,工业物联网,3
|
||||||
|
79,PTC,2.1.3.1,物联网服务,126,华为,2.1.3,工业物联网,3
|
||||||
|
32,兰光创新,1.2.3,数据互通,106,阿里巴巴,1.2,工业互联网网络,3
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,3
|
||||||
|
169,中芯国际,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
47,首自信,2.1.3.6,微服务,108,百度,2.1.3,工业物联网,2
|
||||||
|
74,HoneyWell,1.3.3.2,分布式控制系统DCS,97,General Electric,1.3.3,生产制造,2
|
||||||
|
72,ANSYS,1.3.1.2,计算机辅助工程CAE,99,Siemens,1.3.1,设计研发,2
|
||||||
|
57,亚控科技,2.3.2,边缘数据处理,155,小米,2.3,边缘层,2
|
||||||
|
22,航天云网,2.1.3.7,制造类API,106,阿里巴巴,2.1.3,工业物联网,2
|
||||||
|
71,Altair,1.3.1.2,计算机辅助工程CAE,99,Siemens,1.3.1,设计研发,2
|
||||||
|
47,首自信,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
70,ABB,1.3.3.2,分布式控制系统DCS,99,Siemens,1.3.3,生产制造,2
|
||||||
|
22,航天云网,2.1.3.6,微服务,106,阿里巴巴,2.1.3,工业物联网,2
|
||||||
|
104,Infineon,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
57,亚控科技,2.3.3,协议转换,155,小米,2.3,边缘层,2
|
||||||
|
57,亚控科技,2.3.3,协议转换,99,Siemens,2.3,边缘层,2
|
||||||
|
47,首自信,2.1.3.6,微服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
22,航天云网,2.1.3.4,应用管理服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
22,航天云网,2.1.3.3,工业引擎服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
48,曙光信息,1.2.2,标识解析,126,华为,1.2,工业互联网网络,2
|
||||||
|
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,99,Siemens,1.3.1,设计研发,2
|
||||||
|
49,数码大方,1.3.1.1,计算机辅助设计CAD,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
78,OutSystems,2.1.1.1,算法建模工具,85,Dassault,2.1.1,开发工具,2
|
||||||
|
57,亚控科技,2.3.1,工业数据接入,99,Siemens,2.3,边缘层,2
|
||||||
|
6,安世亚太,2.1.2.1,数据算法模型,159,徐工集团,2.1.2,工业模型库,2
|
||||||
|
78,OutSystems,2.1.1.2,低代码开发工具,148,腾讯,2.1.1,开发工具,2
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,108,百度,2.1.3,工业物联网,2
|
||||||
|
168,中控技术,1.3.3.4,可编程逻揖控制系统PLC,97,General Electric,1.3.3,生产制造,2
|
||||||
|
135,浪潮,2.1.3.3,工业引擎服务,126,华为,2.1.3,工业物联网,2
|
||||||
|
135,浪潮,2.1.3.4,应用管理服务,108,百度,2.1.3,工业物联网,2
|
||||||
|
167,中环股份,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,2
|
||||||
|
79,PTC,2.1.3.1,物联网服务,73,FANUC,2.1.3,工业物联网,2
|
||||||
|
168,中控技术,1.3.3.2,分布式控制系统DCS,75,IBM,1.3.3,生产制造,2
|
||||||
|
22,航天云网,2.3.3,协议转换,99,Siemens,2.3,边缘层,2
|
||||||
|
79,PTC,1.3.1.4,计算机辅助工艺过程设计CAPP,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
138,启明信息,1.3.1.5,产品数据管理PDM,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
14,东华软件,1.3.3.4,可编程逻揖控制系统PLC,75,IBM,1.3.3,生产制造,2
|
||||||
|
167,中环股份,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,2
|
||||||
|
166,中国电子科技网络信息安全,1.2.3,数据互通,67,中国移动,1.2,工业互联网网络,2
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
47,首自信,2.1.2.1,数据算法模型,58,用友,2.1.2,工业模型库,2
|
||||||
|
117,格创东智,2.1.1.3,流程开发工具,85,Dassault,2.1.1,开发工具,2
|
||||||
|
22,航天云网,2.3.1,工业数据接入,95,Schneider,2.3,边缘层,2
|
||||||
|
47,首自信,2.1.2.1,数据算法模型,84,Bosch,2.1.2,工业模型库,2
|
||||||
|
49,数码大方,1.3.1.1,计算机辅助设计CAD,39,Autodesk,1.3.1,设计研发,2
|
||||||
|
165,智能云科,2.1.2.1,数据算法模型,81,SAP,2.1.2,工业模型库,2
|
||||||
|
58,用友,1.3.1.6,产品生命周期管理PLM,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
153,武汉开目,1.3.1.4,计算机辅助工艺过程设计CAPP,39,Autodesk,1.3.1,设计研发,2
|
||||||
|
60,宇动源,2.1.1.4,组态建模工具,80,Salesforce,2.1.1,开发工具,2
|
||||||
|
49,数码大方,2.1.2.2,业务流程模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
60,宇动源,2.1.1.2,低代码开发工具,106,阿里巴巴,2.1.1,开发工具,2
|
||||||
|
115,富士康,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
16,东土科技,1.1.3,工业服务器,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
16,东土科技,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
161,研华科技,2.3.3,协议转换,95,Schneider,2.3,边缘层,2
|
||||||
|
6,安世亚太,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
6,安世亚太,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,2
|
||||||
|
16,东土科技,2.3.1,工业数据接入,99,Siemens,2.3,边缘层,2
|
||||||
|
16,东土科技,2.3.2,边缘数据处理,124,海尔,2.3,边缘层,2
|
||||||
|
6,安世亚太,2.1.2.3,研发仿真模型,84,Bosch,2.1.2,工业模型库,2
|
||||||
|
6,安世亚太,2.1.2.3,研发仿真模型,81,SAP,2.1.2,工业模型库,2
|
||||||
|
161,研华科技,2.3.3,协议转换,155,小米,2.3,边缘层,2
|
||||||
|
16,东土科技,2.3.3,协议转换,95,Schneider,2.3,边缘层,2
|
||||||
|
6,安世亚太,2.1.2.2,业务流程模型,58,用友,2.1.2,工业模型库,2
|
||||||
|
169,中芯国际,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
6,安世亚太,2.1.2.1,数据算法模型,81,SAP,2.1.2,工业模型库,2
|
||||||
|
49,数码大方,2.1.2.1,数据算法模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,93,Cadence,1.3.1,设计研发,2
|
||||||
|
61,元年科技,1.3.3.3,数据采集与监视控制系统SCADA,97,General Electric,1.3.3,生产制造,2
|
||||||
|
135,浪潮,2.1.3.1,物联网服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
49,数码大方,1.3.1.1,计算机辅助设计CAD,99,Siemens,1.3.1,设计研发,2
|
||||||
|
147,拓邦股份,1.1.2,工业控制器,105,Intel,1.1,工业自动化,2
|
||||||
|
168,中控技术,2.3.3,协议转换,126,华为,2.3,边缘层,2
|
||||||
|
147,拓邦股份,1.1.2,工业控制器,94,Mitsubishi,1.1,工业自动化,2
|
||||||
|
64,中电智科,1.1.2,工业控制器,105,Intel,1.1,工业自动化,2
|
||||||
|
149,天泽智云,2.1.2.2,业务流程模型,81,SAP,2.1.2,工业模型库,2
|
||||||
|
101,Analog Devices,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
149,天泽智云,2.1.2.3,研发仿真模型,159,徐工集团,2.1.2,工业模型库,2
|
||||||
|
62,云道智造,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,2
|
||||||
|
22,航天云网,1.2.2,标识解析,126,华为,1.2,工业互联网网络,2
|
||||||
|
49,数码大方,1.3.1.6,产品生命周期管理PLM,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
62,云道智造,2.1.2.2,业务流程模型,58,用友,2.1.2,工业模型库,2
|
||||||
|
106,阿里巴巴,1.3,工业软件,170,Pseudo1,1,供给,2
|
||||||
|
22,航天云网,2.1.1.2,低代码开发工具,106,阿里巴巴,2.1.1,开发工具,2
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,2
|
||||||
|
49,数码大方,1.3.3.1,制造执行系统MES,97,General Electric,1.3.3,生产制造,2
|
||||||
|
33,蓝谷信息,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
22,航天云网,1.3.3.6,运维保障系统MRO,99,Siemens,1.3.3,生产制造,2
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,2
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
82,Uptake,2.1.2.2,业务流程模型,79,PTC,2.1.2,工业模型库,2
|
||||||
|
38,牛刀,2.1.1.5,数字孪生建模工具,148,腾讯,2.1.1,开发工具,2
|
||||||
|
26,寄云科技,2.1.3.3,工业引擎服务,126,华为,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,2.1.3.5,容器服务,74,HoneyWell,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,2.1.3.5,容器服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
9,北京航天测控,1.3.3.6,运维保障系统MRO,97,General Electric,1.3.3,生产制造,2
|
||||||
|
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,39,Autodesk,1.3.1,设计研发,2
|
||||||
|
26,寄云科技,2.1.3.1,物联网服务,106,阿里巴巴,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,2.1.3.7,制造类API,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,2.1.3.7,制造类API,74,HoneyWell,2.1.3,工业物联网,2
|
||||||
|
127,华为海思,1.1.3,工业服务器,126,华为,1.1,工业自动化,2
|
||||||
|
24,华大电子,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
90,Mentor Graphics,1.3.1.7,电子设计自动化EDA,99,Siemens,1.3.1,设计研发,2
|
||||||
|
79,PTC,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,2
|
||||||
|
44,圣邦微电子,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
127,华为海思,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,2
|
||||||
|
13,东方国信,2.1.3.5,容器服务,126,华为,2.1.3,工业物联网,2
|
||||||
|
111,鼎捷软件,1.3.1.6,产品生命周期管理PLM,99,Siemens,1.3.1,设计研发,2
|
||||||
|
31,昆仑数据,1.3.3.3,数据采集与监视控制系统SCADA,99,Siemens,1.3.3,生产制造,2
|
||||||
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,39,Autodesk,1.3.1,设计研发,2
|
||||||
|
29,京东工业品,1.3,工业软件,170,Pseudo1,1,供给,2
|
||||||
|
87,Texas Instruments,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,2
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,73,FANUC,2.1.3,工业物联网,2
|
||||||
|
3,艾克斯特,1.3.1.4,计算机辅助工艺过程设计CAPP,85,Dassault,1.3.1,设计研发,2
|
||||||
|
88,HPE,1.1.3,工业服务器,94,Mitsubishi,1.1,工业自动化,2
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,106,阿里巴巴,2.1.3,工业物联网,2
|
||||||
|
4,爱创科技,1.2.2,标识解析,97,General Electric,1.2,工业互联网网络,2
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
82,Uptake,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,2
|
||||||
|
113,飞腾信息,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,2
|
||||||
|
89,Rockwell,1.1.2,工业控制器,86,Dell EMC,1.1,工业自动化,2
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,108,百度,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,1.2.2,标识解析,106,阿里巴巴,1.2,工业互联网网络,2
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
129,华中数控,1.1.2,工业控制器,94,Mitsubishi,1.1,工业自动化,2
|
||||||
|
79,PTC,2.3.1,工业数据接入,126,华为,2.3,边缘层,2
|
||||||
|
127,华为海思,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,2
|
||||||
|
79,PTC,2.3.1,工业数据接入,124,海尔,2.3,边缘层,2
|
||||||
|
123,海得控制,1.1.2,工业控制器,126,华为,1.1,工业自动化,2
|
||||||
|
131,九物互联,2.1.1.4,组态建模工具,80,Salesforce,2.1.1,开发工具,2
|
||||||
|
38,牛刀,2.1.1.2,低代码开发工具,148,腾讯,2.1.1,开发工具,2
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,148,腾讯,2.1.3,工业物联网,2
|
||||||
|
23,和利时,2.3.1,工业数据接入,95,Schneider,2.3,边缘层,2
|
||||||
|
99,Siemens,1.1.2,工业控制器,105,Intel,1.1,工业自动化,2
|
||||||
|
23,和利时,2.1.3.6,微服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
120,广州数控,1.2.3,数据互通,126,华为,1.2,工业互联网网络,2
|
||||||
|
99,Siemens,1.3.1,设计研发,106,阿里巴巴,1.3,工业软件,2
|
||||||
|
35,凌昊智能,1.1.3,工业服务器,105,Intel,1.1,工业自动化,2
|
||||||
|
135,浪潮,1.1.3,工业服务器,94,Mitsubishi,1.1,工业自动化,2
|
||||||
|
113,飞腾信息,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,2
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,126,华为,2.1.3,工业物联网,2
|
||||||
|
34,力控科技,1.3.3.3,数据采集与监视控制系统SCADA,75,IBM,1.3.3,生产制造,2
|
||||||
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,2
|
||||||
|
117,格创东智,2.1.1.4,组态建模工具,80,Salesforce,2.1.1,开发工具,2
|
||||||
|
79,PTC,2.1.3.5,容器服务,106,阿里巴巴,2.1.3,工业物联网,2
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
23,和利时,2.3.2,边缘数据处理,155,小米,2.3,边缘层,2
|
||||||
|
95,Schneider,1.2.3,数据互通,126,华为,1.2,工业互联网网络,2
|
||||||
|
79,PTC,2.1.3.7,制造类API,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
95,Schneider,1.2.3,数据互通,67,中国移动,1.2,工业互联网网络,2
|
||||||
|
38,牛刀,2.1.1.1,算法建模工具,106,阿里巴巴,2.1.1,开发工具,2
|
||||||
|
79,PTC,2.1.3.5,容器服务,74,HoneyWell,2.1.3,工业物联网,2
|
||||||
|
79,PTC,2.1.3.5,容器服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
79,PTC,2.1.3.6,微服务,97,General Electric,2.1.3,工业物联网,2
|
||||||
|
109,宝信软件,1.3.3.1,制造执行系统MES,97,General Electric,1.3.3,生产制造,1
|
||||||
|
104,Infineon,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
49,数码大方,2.1.2.3,研发仿真模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
36,龙芯中科,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
108,百度,2.2,IaaS,102,Amazon AWS,2,工业互联网平台,1
|
||||||
|
49,数码大方,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
35,凌昊智能,1.1.3,工业服务器,126,华为,1.1,工业自动化,1
|
||||||
|
49,数码大方,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
104,Infineon,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,1
|
||||||
|
38,牛刀,2.1.1.3,流程开发工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
39,Autodesk,1.3.1,设计研发,106,阿里巴巴,1.3,工业软件,1
|
||||||
|
36,龙芯中科,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
36,龙芯中科,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
38,牛刀,2.1.1.5,数字孪生建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
35,凌昊智能,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
38,牛刀,2.1.1.5,数字孪生建模工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
50,索为系统,1.3.1.5,产品数据管理PDM,85,Dassault,1.3.1,设计研发,1
|
||||||
|
38,牛刀,2.1.1.4,组态建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
50,索为系统,1.3.1.5,产品数据管理PDM,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,85,Dassault,1.3.1,设计研发,1
|
||||||
|
39,Autodesk,1.3.1,设计研发,29,京东工业品,1.3,工业软件,1
|
||||||
|
45,石化盈科,2.1.4.1.4,时序数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
45,石化盈科,1.3.3.1,制造执行系统MES,97,General Electric,1.3.3,生产制造,1
|
||||||
|
45,石化盈科,1.3.4.1,企业资源计划ERP,81,SAP,1.3.4,企业运营管理,1
|
||||||
|
47,首自信,2.1.2.2,业务流程模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
47,首自信,2.1.2.2,业务流程模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
45,石化盈科,2.1.4.1.2,分布式数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
45,石化盈科,2.1.4.1.3,实时数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
47,首自信,2.1.2.1,数据算法模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
47,首自信,2.1.2.1,数据算法模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
47,首自信,2.1.1.4,组态建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
47,首自信,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
47,首自信,2.1.1.3,流程开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
47,首自信,2.1.1.2,低代码开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
45,石化盈科,2.1.4.2.1,数据质量管理,79,PTC,2.1.4.2,工业大数据管理,1
|
||||||
|
47,首自信,2.1.1.2,低代码开发工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
47,首自信,2.1.1.2,低代码开发工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
47,首自信,2.1.1.1,算法建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
45,石化盈科,2.1.4.2.2,数据安全管理,79,PTC,2.1.4.2,工业大数据管理,1
|
||||||
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,93,Cadence,1.3.1,设计研发,1
|
||||||
|
47,首自信,2.1.2.3,研发仿真模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
44,圣邦微电子,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
49,数码大方,2.1.2.2,业务流程模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,85,Dassault,1.3.1,设计研发,1
|
||||||
|
4,爱创科技,1.2.2,标识解析,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
49,数码大方,2.1.2.1,数据算法模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
111,鼎捷软件,1.3.4.1,企业资源计划ERP,81,SAP,1.3.4,企业运营管理,1
|
||||||
|
49,数码大方,1.3.3.1,制造执行系统MES,99,Siemens,1.3.3,生产制造,1
|
||||||
|
111,鼎捷软件,1.3.4.1,企业资源计划ERP,77,Oracle,1.3.4,企业运营管理,1
|
||||||
|
111,鼎捷软件,1.3.3.1,制造执行系统MES,99,Siemens,1.3.3,生产制造,1
|
||||||
|
49,数码大方,1.3.1.6,产品生命周期管理PLM,99,Siemens,1.3.1,设计研发,1
|
||||||
|
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,99,Siemens,1.3.1,设计研发,1
|
||||||
|
111,鼎捷软件,1.3.1.6,产品生命周期管理PLM,85,Dassault,1.3.1,设计研发,1
|
||||||
|
47,首自信,2.1.3.6,微服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
42,山大华天,1.3.1.1,计算机辅助设计CAD,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
42,山大华天,1.3.1.3,计算机辅助制造CAM,99,Siemens,1.3.1,设计研发,1
|
||||||
|
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,85,Dassault,1.3.1,设计研发,1
|
||||||
|
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,99,Siemens,1.3.1,设计研发,1
|
||||||
|
47,首自信,2.1.3.6,微服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
43,神舟软件,1.3.1.5,产品数据管理PDM,93,Cadence,1.3.1,设计研发,1
|
||||||
|
43,神舟软件,1.3.1.6,产品生命周期管理PLM,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
119,广联达,1.3.1.1,计算机辅助设计CAD,85,Dassault,1.3.1,设计研发,1
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
82,Uptake,2.1.2.1,数据算法模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
81,SAP,2.1.4.2,工业大数据管理,115,富士康,2.1.4,工业大数据,1
|
||||||
|
81,SAP,2.1.4.2,工业大数据管理,102,Amazon AWS,2.1.4,工业大数据,1
|
||||||
|
81,SAP,2.1.4.1,工业大数据存储,102,Amazon AWS,2.1.4,工业大数据,1
|
||||||
|
80,Salesforce,1.3.4,企业运营管理,29,京东工业品,1.3,工业软件,1
|
||||||
|
79,PTC,2.3.3,协议转换,95,Schneider,2.3,边缘层,1
|
||||||
|
79,PTC,2.3.3,协议转换,84,Bosch,2.3,边缘层,1
|
||||||
|
79,PTC,2.3.3,协议转换,155,小米,2.3,边缘层,1
|
||||||
|
79,PTC,2.3.3,协议转换,102,Amazon AWS,2,工业互联网平台,1
|
||||||
|
79,PTC,2.3.2,边缘数据处理,126,华为,2.3,边缘层,1
|
||||||
|
79,PTC,2.3.1,工业数据接入,95,Schneider,2.3,边缘层,1
|
||||||
|
79,PTC,2.3.1,工业数据接入,84,Bosch,2.3,边缘层,1
|
||||||
|
79,PTC,2.1.3.7,制造类API,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.7,制造类API,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.6,微服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.6,微服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.5,容器服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.5,容器服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
79,PTC,2.1.3.1,物联网服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
79,PTC,1.3.1.6,产品生命周期管理PLM,93,Cadence,1.3.1,设计研发,1
|
||||||
|
81,SAP,2.1.4.2,工业大数据管理,84,Bosch,2.1.4,工业大数据,1
|
||||||
|
82,Uptake,2.1.2.1,数据算法模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
79,PTC,1.3.1.6,产品生命周期管理PLM,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
82,Uptake,2.1.2.1,数据算法模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
10,北京英贝思,1.3.3.5,企业资产管理系统EAM,75,IBM,1.3.3,生产制造,1
|
||||||
|
10,北京英贝思,1.3.3.5,企业资产管理系统EAM,99,Siemens,1.3.3,生产制造,1
|
||||||
|
99,Siemens,1.2.1,网络互联,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
100,Synopsys,1.3.1,设计研发,29,京东工业品,1.3,工业软件,1
|
||||||
|
97,General Electric,1.3.3,生产制造,29,京东工业品,1.3,工业软件,1
|
||||||
|
96,Cisco,1.2.3,数据互通,126,华为,1.2,工业互联网网络,1
|
||||||
|
95,Schneider,2.3,边缘层,98,Microsoft Azure,2,工业互联网平台,1
|
||||||
|
93,Cadence,1.3.1,设计研发,29,京东工业品,1.3,工业软件,1
|
||||||
|
93,Cadence,1.3.1,设计研发,106,阿里巴巴,1.3,工业软件,1
|
||||||
|
92,Omron,1.3.3.4,可编程逻揖控制系统PLC,97,General Electric,1.3.3,生产制造,1
|
||||||
|
91,Moxa,1.2.1,网络互联,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
90,Mentor Graphics,1.3.1.7,电子设计自动化EDA,85,Dassault,1.3.1,设计研发,1
|
||||||
|
9,北京航天测控,1.3.3.6,运维保障系统MRO,75,IBM,1.3.3,生产制造,1
|
||||||
|
89,Rockwell,1.3.3.1,制造执行系统MES,75,IBM,1.3.3,生产制造,1
|
||||||
|
89,Rockwell,1.2.1,网络互联,97,General Electric,1.2,工业互联网网络,1
|
||||||
|
89,Rockwell,1.2.1,网络互联,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
89,Rockwell,1.1.2,工业控制器,126,华为,1.1,工业自动化,1
|
||||||
|
88,HPE,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
87,Texas Instruments,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
85,Dassault,1.3.1,设计研发,106,阿里巴巴,1.3,工业软件,1
|
||||||
|
83,Emerson,1.3.3.2,分布式控制系统DCS,99,Siemens,1.3.3,生产制造,1
|
||||||
|
83,Emerson,1.3.3.2,分布式控制系统DCS,75,IBM,1.3.3,生产制造,1
|
||||||
|
82,Uptake,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
82,Uptake,2.1.2.4,行业机理模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
82,Uptake,2.1.2.3,研发仿真模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
82,Uptake,2.1.2.3,研发仿真模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
82,Uptake,2.1.2.2,业务流程模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
79,PTC,1.3.1.6,产品生命周期管理PLM,85,Dassault,1.3.1,设计研发,1
|
||||||
|
79,PTC,1.3.1.4,计算机辅助工艺过程设计CAPP,99,Siemens,1.3.1,设计研发,1
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
62,云道智造,2.1.2.1,数据算法模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
62,云道智造,1.3.1.2,计算机辅助工程CAE,99,Siemens,1.3.1,设计研发,1
|
||||||
|
62,云道智造,1.3.1.2,计算机辅助工程CAE,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
62,云道智造,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
60,宇动源,2.1.1.5,数字孪生建模工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.5,数字孪生建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.3,流程开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.2,低代码开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.1,算法建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.1,算法建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
60,宇动源,2.1.1.1,算法建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
6,安世亚太,2.1.2.2,业务流程模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
6,安世亚太,2.1.2.2,业务流程模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
6,安世亚太,2.1.2.1,数据算法模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
6,安世亚太,1.3.1.2,计算机辅助工程CAE,99,Siemens,1.3.1,设计研发,1
|
||||||
|
6,安世亚太,1.3.1.2,计算机辅助工程CAE,85,Dassault,1.3.1,设计研发,1
|
||||||
|
6,安世亚太,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,1
|
||||||
|
58,用友,1.3.2,采购供应,170,Pseudo1,1,供给,1
|
||||||
|
58,用友,1.2.2,标识解析,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
58,用友,1.2.2,标识解析,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
57,亚控科技,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,1
|
||||||
|
57,亚控科技,2.3.2,边缘数据处理,126,华为,2.3,边缘层,1
|
||||||
|
57,亚控科技,2.3.1,工业数据接入,126,华为,2.3,边缘层,1
|
||||||
|
57,亚控科技,1.3.3.3,数据采集与监视控制系统SCADA,99,Siemens,1.3.3,生产制造,1
|
||||||
|
57,亚控科技,1.3.3.3,数据采集与监视控制系统SCADA,97,General Electric,1.3.3,生产制造,1
|
||||||
|
56,芯愿景,1.3.1.7,电子设计自动化EDA,93,Cadence,1.3.1,设计研发,1
|
||||||
|
56,芯愿景,1.3.1.7,电子设计自动化EDA,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
62,云道智造,2.1.2.1,数据算法模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
62,云道智造,2.1.2.2,业务流程模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
79,PTC,1.3.1.1,计算机辅助设计CAD,99,Siemens,1.3.1,设计研发,1
|
||||||
|
62,云道智造,2.1.2.2,业务流程模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
79,PTC,1.3.1.1,计算机辅助设计CAD,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
79,PTC,1.3.1.1,计算机辅助设计CAD,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
78,OutSystems,2.1.1.5,数字孪生建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
78,OutSystems,2.1.1.3,流程开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
78,OutSystems,2.1.1.3,流程开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
78,OutSystems,2.1.1.2,低代码开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
78,OutSystems,2.1.1.2,低代码开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
77,Oracle,1.3.3.6,运维保障系统MRO,99,Siemens,1.3.3,生产制造,1
|
||||||
|
77,Oracle,1.3.3.6,运维保障系统MRO,97,General Electric,1.3.3,生产制造,1
|
||||||
|
72,ANSYS,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
71,Altair,1.3.1.2,计算机辅助工程CAE,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
71,Altair,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
70,ABB,1.3.3.4,可编程逻揖控制系统PLC,97,General Electric,1.3.3,生产制造,1
|
||||||
|
69,紫光集团,1.1.1,工业计算芯片,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
69,紫光集团,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
68,中望软件,1.3.1.2,计算机辅助工程CAE,99,Siemens,1.3.1,设计研发,1
|
||||||
|
68,中望软件,1.3.1.1,计算机辅助设计CAD,99,Siemens,1.3.1,设计研发,1
|
||||||
|
68,中望软件,1.3.1.1,计算机辅助设计CAD,93,Cadence,1.3.1,设计研发,1
|
||||||
|
68,中望软件,1.3.1.1,计算机辅助设计CAD,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
66,中国联通,1.2.1,网络互联,126,华为,1.2,工业互联网网络,1
|
||||||
|
65,中国电信,1.2.1,网络互联,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
65,中国电信,1.2.1,网络互联,126,华为,1.2,工业互联网网络,1
|
||||||
|
65,中国电信,1.2.1,网络互联,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
64,中电智科,1.1.2,工业控制器,126,华为,1.1,工业自动化,1
|
||||||
|
101,Analog Devices,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
62,云道智造,2.1.2.4,行业机理模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
62,云道智造,2.1.2.3,研发仿真模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
33,蓝谷信息,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
23,和利时,2.3.3,协议转换,99,Siemens,2.3,边缘层,1
|
||||||
|
33,蓝谷信息,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
137,美林数据,2.1.4.1.3,实时数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
135,浪潮,2.1.3.6,微服务,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.7,制造类API,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.7,制造类API,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.7,制造类API,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.7,制造类API,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.2,IaaS,102,Amazon AWS,2,工业互联网平台,1
|
||||||
|
137,美林数据,2.1.4.2.1,数据质量管理,81,SAP,2.1.4.2,工业大数据管理,1
|
||||||
|
135,浪潮,2.1.3.5,容器服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
139,容知日新,1.3.3.7,故障预测与健康管理PHM,99,Siemens,1.3.3,生产制造,1
|
||||||
|
14,东华软件,1.3.4.3,人力资源管理HRM,80,Salesforce,1.3.4,企业运营管理,1
|
||||||
|
117,格创东智,2.1.1.2,低代码开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
117,格创东智,2.1.1.2,低代码开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
141,上海新华控制,1.3.3.2,分布式控制系统DCS,75,IBM,1.3.3,生产制造,1
|
||||||
|
141,上海新华控制,1.3.3.2,分布式控制系统DCS,99,Siemens,1.3.3,生产制造,1
|
||||||
|
135,浪潮,2.1.3.6,微服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.5,容器服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
116,概伦电子,1.3.1.7,电子设计自动化EDA,93,Cadence,1.3.1,设计研发,1
|
||||||
|
117,格创东智,2.1.1.5,数字孪生建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
131,九物互联,2.1.1.4,组态建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
132,科远智慧,1.3.3.2,分布式控制系统DCS,97,General Electric,1.3.3,生产制造,1
|
||||||
|
133,蓝盾股份,1.4.4.1,身份鉴别与访问控制,40,奇安信,1.4.4,平台安全,1
|
||||||
|
134,朗坤智慧,1.3.3.5,企业资产管理系统EAM,75,IBM,1.3.3,生产制造,1
|
||||||
|
134,朗坤智慧,1.3.3.5,企业资产管理系统EAM,97,General Electric,1.3.3,生产制造,1
|
||||||
|
135,浪潮,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
117,格创东智,2.1.1.4,组态建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
135,浪潮,2.1.3.4,应用管理服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,170,Pseudo1,1,供给,1
|
||||||
|
117,格创东智,2.1.1.4,组态建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
135,浪潮,1.3.4.1,企业资源计划ERP,81,SAP,1.3.4,企业运营管理,1
|
||||||
|
135,浪潮,2.1.3.2,平台基础服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.2,平台基础服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
135,浪潮,2.1.3.3,工业引擎服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
117,格创东智,2.1.1.2,低代码开发工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
116,概伦电子,1.3.1.7,电子设计自动化EDA,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
149,天泽智云,2.1.2.3,研发仿真模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,85,Dassault,1.3.1,设计研发,1
|
||||||
|
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,93,Cadence,1.3.1,设计研发,1
|
||||||
|
149,天泽智云,2.1.2.1,数据算法模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.1,数据算法模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.2,业务流程模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.3,研发仿真模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
149,天泽智云,2.1.2.4,行业机理模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
149,天泽智云,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
15,东软集团,1.3.3.5,企业资产管理系统EAM,75,IBM,1.3.3,生产制造,1
|
||||||
|
15,东软集团,1.3.3.5,企业资产管理系统EAM,99,Siemens,1.3.3,生产制造,1
|
||||||
|
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,85,Dassault,1.3.1,设计研发,1
|
||||||
|
144,树根互联,2.1.2.4,行业机理模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.2,低代码开发工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.5,数字孪生建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.2,低代码开发工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.3,流程开发工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.3,流程开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.4,组态建模工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.4,组态建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
143,沈阳自动化研究所,2.1.1.5,数字孪生建模工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
144,树根互联,2.1.2.1,数据算法模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.1,数据算法模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.2,业务流程模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.2,业务流程模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.3,研发仿真模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.3,研发仿真模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
144,树根互联,2.1.2.4,行业机理模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
131,九物互联,2.1.1.3,流程开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
131,九物互联,2.1.1.1,算法建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
131,九物互联,2.1.1.1,算法建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
128,华伍股份,1.1.2,工业控制器,126,华为,1.1,工业自动化,1
|
||||||
|
129,华中数控,1.1.2,工业控制器,105,Intel,1.1,工业自动化,1
|
||||||
|
129,华中数控,1.1.2,工业控制器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
129,华中数控,1.2.3,数据互通,97,General Electric,1.2,工业互联网网络,1
|
||||||
|
13,东方国信,1.2.2,标识解析,126,华为,1.2,工业互联网网络,1
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
127,华为海思,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
128,华伍股份,1.1.2,工业控制器,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
127,华为海思,1.1.1,工业计算芯片,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
117,格创东智,2.1.1.5,数字孪生建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
123,海得控制,1.1.2,工业控制器,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
119,广联达,1.3.1.1,计算机辅助设计CAD,99,Siemens,1.3.1,设计研发,1
|
||||||
|
12,大唐软件,1.2.1,网络互联,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
12,大唐软件,1.2.1,网络互联,126,华为,1.2,工业互联网网络,1
|
||||||
|
12,大唐软件,1.2.1,网络互联,97,General Electric,1.2,工业互联网网络,1
|
||||||
|
120,广州数控,1.2.3,数据互通,67,中国移动,1.2,工业互联网网络,1
|
||||||
|
123,海得控制,1.1.2,工业控制器,105,Intel,1.1,工业自动化,1
|
||||||
|
124,海尔,1.2.1,网络互联,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
126,华为,2.3,边缘层,102,Amazon AWS,2,工业互联网平台,1
|
||||||
|
124,海尔,1.2.1,网络互联,126,华为,1.2,工业互联网网络,1
|
||||||
|
124,海尔,2.3,边缘层,98,Microsoft Azure,2,工业互联网平台,1
|
||||||
|
125,华数机器人,1.2.3,数据互通,126,华为,1.2,工业互联网网络,1
|
||||||
|
118,工邦邦,1.3.3.6,运维保障系统MRO,75,IBM,1.3.3,生产制造,1
|
||||||
|
126,华为,2.1.1.5,数字孪生建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
126,华为,2.2,IaaS,102,Amazon AWS,2,工业互联网平台,1
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.3.3,协议转换,124,海尔,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.1,工业数据接入,95,Schneider,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,124,海尔,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,126,华为,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,155,小米,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,95,Schneider,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.3,协议转换,155,小米,2.3,边缘层,1
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
117,格创东智,2.1.4.2.2,数据安全管理,79,PTC,2.1.4.2,工业大数据管理,1
|
||||||
|
130,金蝶,1.3.2,采购供应,170,Pseudo1,1,供给,1
|
||||||
|
117,格创东智,2.1.4.2.1,数据质量管理,81,SAP,2.1.4.2,工业大数据管理,1
|
||||||
|
130,金蝶,1.3.4.1,企业资源计划ERP,77,Oracle,1.3.4,企业运营管理,1
|
||||||
|
117,格创东智,2.1.4.1.1,关系型数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
130,金蝶,1.3.5,仓储物流,170,Pseudo1,1,供给,1
|
||||||
|
13,东方国信,2.3.1,工业数据接入,155,小米,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.1,工业数据接入,126,华为,2.3,边缘层,1
|
||||||
|
13,东方国信,2.3.1,工业数据接入,124,海尔,2.3,边缘层,1
|
||||||
|
13,东方国信,2.1.4.2.1,数据质量管理,81,SAP,2.1.4.2,工业大数据管理,1
|
||||||
|
13,东方国信,2.1.4.1.4,时序数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
13,东方国信,2.1.4.1.4,时序数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
13,东方国信,2.1.4.1.2,分布式数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
13,东方国信,2.1.3.7,制造类API,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.7,制造类API,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.6,微服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.6,微服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.6,微服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.6,微服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.5,容器服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.5,容器服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.5,容器服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
13,东方国信,2.1.3.5,容器服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
33,蓝谷信息,2.1.2.3,研发仿真模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
23,和利时,1.3.3.4,可编程逻揖控制系统PLC,99,Siemens,1.3.3,生产制造,1
|
||||||
|
22,航天云网,2.3.3,协议转换,95,Schneider,2.3,边缘层,1
|
||||||
|
23,和利时,1.3.3.1,制造执行系统MES,75,IBM,1.3.3,生产制造,1
|
||||||
|
23,和利时,1.3.3.1,制造执行系统MES,99,Siemens,1.3.3,生产制造,1
|
||||||
|
23,和利时,1.3.3.2,分布式控制系统DCS,75,IBM,1.3.3,生产制造,1
|
||||||
|
23,和利时,1.3.3.3,数据采集与监视控制系统SCADA,75,IBM,1.3.3,生产制造,1
|
||||||
|
23,和利时,1.3.3.3,数据采集与监视控制系统SCADA,99,Siemens,1.3.3,生产制造,1
|
||||||
|
115,富士康,1.1.3,工业服务器,105,Intel,1.1,工业自动化,1
|
||||||
|
22,航天云网,2.3.3,协议转换,126,华为,2.3,边缘层,1
|
||||||
|
113,飞腾信息,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
23,和利时,2.1.3.6,微服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
23,和利时,2.3.1,工业数据接入,99,Siemens,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.2,边缘数据处理,124,海尔,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.3,协议转换,124,海尔,2.3,边缘层,1
|
||||||
|
1,51WORLD,2.1.1.5,数字孪生建模工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
22,航天云网,2.3.2,边缘数据处理,84,Bosch,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.3,协议转换,84,Bosch,2.3,边缘层,1
|
||||||
|
22,航天云网,2.1.3.5,容器服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.1,物联网服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.2,平台基础服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.3,工业引擎服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.4,应用管理服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.4,应用管理服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.5,容器服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.6,微服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.3.2,边缘数据处理,155,小米,2.3,边缘层,1
|
||||||
|
22,航天云网,2.1.3.6,微服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.6,微服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.7,制造类API,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.3.1,工业数据接入,155,小米,2.3,边缘层,1
|
||||||
|
22,航天云网,2.3.1,工业数据接入,84,Bosch,2.3,边缘层,1
|
||||||
|
22,航天云网,2.3.1,工业数据接入,99,Siemens,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.3,协议转换,126,华为,2.3,边缘层,1
|
||||||
|
23,和利时,2.3.3,协议转换,95,Schneider,2.3,边缘层,1
|
||||||
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
31,昆仑数据,2.1.4.1.3,实时数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,85,Dassault,1.3.1,设计研发,1
|
||||||
|
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,99,Siemens,1.3.1,设计研发,1
|
||||||
|
3,艾克斯特,1.3.4.1,企业资源计划ERP,80,Salesforce,1.3.4,企业运营管理,1
|
||||||
|
31,昆仑数据,1.3.3.3,数据采集与监视控制系统SCADA,75,IBM,1.3.3,生产制造,1
|
||||||
|
31,昆仑数据,2.1.4.1.1,关系型数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
31,昆仑数据,2.1.4.2.1,数据质量管理,79,PTC,2.1.4.2,工业大数据管理,1
|
||||||
|
26,寄云科技,2.1.3.7,制造类API,74,HoneyWell,2.1.3,工业物联网,1
|
||||||
|
32,兰光创新,1.2.3,数据互通,97,General Electric,1.2,工业互联网网络,1
|
||||||
|
33,蓝谷信息,2.1.2.1,数据算法模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
33,蓝谷信息,2.1.2.2,业务流程模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
33,蓝谷信息,2.1.2.2,业务流程模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
33,蓝谷信息,2.1.2.2,业务流程模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
33,蓝谷信息,2.1.2.3,研发仿真模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
3,艾克斯特,1.3.1.4,计算机辅助工艺过程设计CAPP,99,Siemens,1.3.1,设计研发,1
|
||||||
|
26,寄云科技,2.1.3.7,制造类API,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
119,广联达,1.3.1.1,计算机辅助设计CAD,93,Cadence,1.3.1,设计研发,1
|
||||||
|
26,寄云科技,2.1.3.2,平台基础服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
24,华大电子,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
24,华大电子,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
25,华大九天,1.3.1.7,电子设计自动化EDA,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
25,华大九天,1.3.1.7,电子设计自动化EDA,85,Dassault,1.3.1,设计研发,1
|
||||||
|
26,寄云科技,2.1.3.1,物联网服务,148,腾讯,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.2,平台基础服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.3,工业引擎服务,108,百度,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.6,微服务,73,FANUC,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.4,应用管理服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.4,应用管理服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.5,容器服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.5,容器服务,97,General Electric,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.6,微服务,106,阿里巴巴,2.1.3,工业物联网,1
|
||||||
|
26,寄云科技,2.1.3.6,微服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.3.1,物联网服务,126,华为,2.1.3,工业物联网,1
|
||||||
|
22,航天云网,2.1.1.5,数字孪生建模工具,80,Salesforce,2.1.1,开发工具,1
|
||||||
|
22,航天云网,2.1.1.5,数字孪生建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
163,优也科技,2.1.4.2.2,数据安全管理,79,PTC,2.1.4.2,工业大数据管理,1
|
||||||
|
161,研华科技,2.3.2,边缘数据处理,155,小米,2.3,边缘层,1
|
||||||
|
161,研华科技,2.3.2,边缘数据处理,84,Bosch,2.3,边缘层,1
|
||||||
|
161,研华科技,2.3.2,边缘数据处理,95,Schneider,2.3,边缘层,1
|
||||||
|
161,研华科技,2.3.3,协议转换,124,海尔,2.3,边缘层,1
|
||||||
|
163,优也科技,2.1.4.1.1,关系型数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
163,优也科技,2.1.4.1.4,时序数据库,81,SAP,2.1.4.1,工业大数据存储,1
|
||||||
|
163,优也科技,2.1.4.2.2,数据安全管理,81,SAP,2.1.4.2,工业大数据管理,1
|
||||||
|
161,研华科技,2.3.1,工业数据接入,84,Bosch,2.3,边缘层,1
|
||||||
|
164,震坤行,1.3.3.6,运维保障系统MRO,75,IBM,1.3.3,生产制造,1
|
||||||
|
164,震坤行,1.3.3.6,运维保障系统MRO,99,Siemens,1.3.3,生产制造,1
|
||||||
|
165,智能云科,2.1.2.1,数据算法模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
165,智能云科,2.1.2.2,业务流程模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
165,智能云科,2.1.2.2,业务流程模型,58,用友,2.1.2,工业模型库,1
|
||||||
|
165,智能云科,2.1.2.2,业务流程模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
161,研华科技,2.3.2,边缘数据处理,124,海尔,2.3,边缘层,1
|
||||||
|
161,研华科技,2.3.1,工业数据接入,126,华为,2.3,边缘层,1
|
||||||
|
22,航天云网,2.1.1.4,组态建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
116,概伦电子,1.3.1.7,电子设计自动化EDA,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,85,Dassault,1.3.1,设计研发,1
|
||||||
|
153,武汉开目,1.3.1.4,计算机辅助工艺过程设计CAPP,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
154,西格数据,2.1.4.1.2,分布式数据库,79,PTC,2.1.4.1,工业大数据存储,1
|
||||||
|
154,西格数据,2.1.4.2.2,数据安全管理,81,SAP,2.1.4.2,工业大数据管理,1
|
||||||
|
156,芯禾科技,1.3.1.7,电子设计自动化EDA,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
156,芯禾科技,1.3.1.7,电子设计自动化EDA,85,Dassault,1.3.1,设计研发,1
|
||||||
|
16,东土科技,1.1.3,工业服务器,94,Mitsubishi,1.1,工业自动化,1
|
||||||
|
161,研华科技,2.3.1,工业数据接入,124,海尔,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.1,工业数据接入,124,海尔,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.1,工业数据接入,126,华为,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.1,工业数据接入,84,Bosch,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.1,工业数据接入,95,Schneider,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.2,边缘数据处理,84,Bosch,2.3,边缘层,1
|
||||||
|
16,东土科技,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,1
|
||||||
|
165,智能云科,2.1.2.2,业务流程模型,84,Bosch,2.1.2,工业模型库,1
|
||||||
|
165,智能云科,2.1.2.3,研发仿真模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
165,智能云科,2.1.2.4,行业机理模型,159,徐工集团,2.1.2,工业模型库,1
|
||||||
|
20,海基科技,1.3.1.2,计算机辅助工程CAE,39,Autodesk,1.3.1,设计研发,1
|
||||||
|
169,中芯国际,1.1.1,工业计算芯片,105,Intel,1.1,工业自动化,1
|
||||||
|
169,中芯国际,1.1.1,工业计算芯片,126,华为,1.1,工业自动化,1
|
||||||
|
18,国能智深,1.3.3.2,分布式控制系统DCS,99,Siemens,1.3.3,生产制造,1
|
||||||
|
2,706所,1.1.3,工业服务器,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
2,706所,1.1.3,工业服务器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
20,海基科技,1.3.1.2,计算机辅助工程CAE,100,Synopsys,1.3.1,设计研发,1
|
||||||
|
20,海基科技,1.3.1.2,计算机辅助工程CAE,93,Cadence,1.3.1,设计研发,1
|
||||||
|
165,智能云科,2.1.2.4,行业机理模型,79,PTC,2.1.2,工业模型库,1
|
||||||
|
21,Hexagon,1.3.1.3,计算机辅助制造CAM,85,Dassault,1.3.1,设计研发,1
|
||||||
|
22,航天云网,1.2.2,标识解析,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
22,航天云网,2.1.1.1,算法建模工具,106,阿里巴巴,2.1.1,开发工具,1
|
||||||
|
22,航天云网,2.1.1.1,算法建模工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
22,航天云网,2.1.1.3,流程开发工具,148,腾讯,2.1.1,开发工具,1
|
||||||
|
22,航天云网,2.1.1.3,流程开发工具,85,Dassault,2.1.1,开发工具,1
|
||||||
|
168,中控技术,2.3.3,协议转换,99,Siemens,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.3,协议转换,84,Bosch,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.3,协议转换,124,海尔,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.2,边缘数据处理,99,Siemens,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.2,边缘数据处理,95,Schneider,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.2,边缘数据处理,155,小米,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.2,边缘数据处理,124,海尔,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.1,工业数据接入,99,Siemens,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.1,工业数据接入,84,Bosch,2.3,边缘层,1
|
||||||
|
168,中控技术,2.3.1,工业数据接入,155,小米,2.3,边缘层,1
|
||||||
|
168,中控技术,1.3.3.2,分布式控制系统DCS,97,General Electric,1.3.3,生产制造,1
|
||||||
|
168,中控技术,1.3.3.1,制造执行系统MES,97,General Electric,1.3.3,生产制造,1
|
||||||
|
168,中控技术,1.1.2,工业控制器,86,Dell EMC,1.1,工业自动化,1
|
||||||
|
168,中控技术,1.1.2,工业控制器,105,Intel,1.1,工业自动化,1
|
||||||
|
167,中环股份,1.1.1,工业计算芯片,106,阿里巴巴,1.1,工业自动化,1
|
||||||
|
166,中国电子科技网络信息安全,1.2.3,数据互通,106,阿里巴巴,1.2,工业互联网网络,1
|
||||||
|
165,智能云科,2.1.2.4,行业机理模型,81,SAP,2.1.2,工业模型库,1
|
||||||
|
22,航天云网,2.3.3,协议转换,84,Bosch,2.3,边缘层,1
|
|
Before Width: | Height: | Size: 568 KiB After Width: | Height: | Size: 568 KiB |
Before Width: | Height: | Size: 531 KiB After Width: | Height: | Size: 531 KiB |
|
@ -0,0 +1,98 @@
|
||||||
|
up_id_product,up_name_product,down_id_product,down_name_product,count
|
||||||
|
1.4,工业互联网安全,1,供给,118
|
||||||
|
1.4.3,网络安全,1.4,工业互联网安全,96
|
||||||
|
1.4.5,数据安全,1.4,工业互联网安全,92
|
||||||
|
1.4.2,控制安全,1.4,工业互联网安全,92
|
||||||
|
2.1,PaaS,2,工业互联网平台,77
|
||||||
|
1.4.4.5,安全态势感知,1.4.4,平台安全,76
|
||||||
|
1.3.2.1,供应链管理SCM,1.3.2,采购供应,76
|
||||||
|
1.3.2,采购供应,1.3,工业软件,74
|
||||||
|
1.3.5,仓储物流,1.3,工业软件,72
|
||||||
|
1.1.1,工业计算芯片,1.1,工业自动化,67
|
||||||
|
1.4.5.8,数据加密,1.4.5,数据安全,50
|
||||||
|
1.4.5.1,恶意代码检测系统,1.4.5,数据安全,50
|
||||||
|
1.4.3.6,沙箱类设备,1.4.3,网络安全,50
|
||||||
|
1.4.2.7,工控原生安全,1.4.2,控制安全,50
|
||||||
|
1.4.2.3,工控漏洞扫描,1.4.2,控制安全,50
|
||||||
|
1.4.1,设备安全,1.4,工业互联网安全,50
|
||||||
|
1.4.3.2,流量检测,1.4.3,网络安全,50
|
||||||
|
2.3.3,协议转换,2.3,边缘层,37
|
||||||
|
1.3.2.1,供应链管理SCM,1.3,工业软件,37
|
||||||
|
2.3.1,工业数据接入,2.3,边缘层,33
|
||||||
|
2.1.3.6,微服务,2.1.3,工业物联网,33
|
||||||
|
2.3.2,边缘数据处理,2.3,边缘层,30
|
||||||
|
2.1.3.4,应用管理服务,2.1.3,工业物联网,30
|
||||||
|
2.1.2.4,行业机理模型,2.1.2,工业模型库,30
|
||||||
|
2.1.2.2,业务流程模型,2.1.2,工业模型库,28
|
||||||
|
2.1.3.7,制造类API,2.1.3,工业物联网,28
|
||||||
|
1.3.1.1,计算机辅助设计CAD,1.3.1,设计研发,28
|
||||||
|
2.1.2.1,数据算法模型,2.1.2,工业模型库,27
|
||||||
|
1.3.1.2,计算机辅助工程CAE,1.3.1,设计研发,26
|
||||||
|
2.1.3.1,物联网服务,2.1.3,工业物联网,25
|
||||||
|
1.1.2,工业控制器,1.1,工业自动化,24
|
||||||
|
2.1.3.5,容器服务,2.1.3,工业物联网,24
|
||||||
|
1.4.3.6,沙箱类设备,1.4,工业互联网安全,23
|
||||||
|
2.1.1.2,低代码开发工具,2.1.1,开发工具,23
|
||||||
|
1.1.3,工业服务器,1.1,工业自动化,23
|
||||||
|
1.4.3.2,流量检测,1.4,工业互联网安全,23
|
||||||
|
2.1.3.3,工业引擎服务,2.1.3,工业物联网,23
|
||||||
|
1.4.5.1,恶意代码检测系统,1.4,工业互联网安全,21
|
||||||
|
1.4.5.8,数据加密,1.4,工业互联网安全,21
|
||||||
|
1.4.2.3,工控漏洞扫描,1.4,工业互联网安全,21
|
||||||
|
2.1.3.2,平台基础服务,2.1.3,工业物联网,21
|
||||||
|
1.4.2.7,工控原生安全,1.4,工业互联网安全,21
|
||||||
|
1.4.3,网络安全,1,供给,21
|
||||||
|
1.3.1.4,计算机辅助工艺过程设计CAPP,1.3.1,设计研发,20
|
||||||
|
1.4.5,数据安全,1,供给,19
|
||||||
|
1.4.2,控制安全,1,供给,19
|
||||||
|
2.1.2.3,研发仿真模型,2.1.2,工业模型库,18
|
||||||
|
2.1.1.5,数字孪生建模工具,2.1.1,开发工具,18
|
||||||
|
1.3.1.6,产品生命周期管理PLM,1.3.1,设计研发,18
|
||||||
|
1.2.3,数据互通,1.2,工业互联网网络,17
|
||||||
|
2.1.1.1,算法建模工具,2.1.1,开发工具,15
|
||||||
|
2.1.1.4,组态建模工具,2.1.1,开发工具,14
|
||||||
|
1.3.3.2,分布式控制系统DCS,1.3.3,生产制造,14
|
||||||
|
1.2.2,标识解析,1.2,工业互联网网络,13
|
||||||
|
1.2.1,网络互联,1.2,工业互联网网络,13
|
||||||
|
2.1.1.3,流程开发工具,2.1.1,开发工具,12
|
||||||
|
1.3.1.7,电子设计自动化EDA,1.3.1,设计研发,12
|
||||||
|
1.3.3.3,数据采集与监视控制系统SCADA,1.3.3,生产制造,11
|
||||||
|
2,工业互联网平台,1,供给,10
|
||||||
|
1.3.3.6,运维保障系统MRO,1.3.3,生产制造,10
|
||||||
|
1.3.3.1,制造执行系统MES,1.3.3,生产制造,10
|
||||||
|
1.4.4,平台安全,1.4,工业互联网安全,10
|
||||||
|
1.4.1,设备安全,1,供给,9
|
||||||
|
1.3.1,设计研发,1.3,工业软件,8
|
||||||
|
1.3.3.4,可编程逻揖控制系统PLC,1.3.3,生产制造,7
|
||||||
|
1.3.4.1,企业资源计划ERP,1.3.4,企业运营管理,6
|
||||||
|
1.3.3.5,企业资产管理系统EAM,1.3.3,生产制造,6
|
||||||
|
1.4.3.6,沙箱类设备,1,供给,6
|
||||||
|
1.4.3.2,流量检测,1,供给,6
|
||||||
|
1.4.5.1,恶意代码检测系统,1,供给,5
|
||||||
|
1.4.4.5,安全态势感知,1.4,工业互联网安全,5
|
||||||
|
2.1,PaaS,1,供给,5
|
||||||
|
1.4.2.7,工控原生安全,1,供给,5
|
||||||
|
1.3.1.5,产品数据管理PDM,1.3.1,设计研发,5
|
||||||
|
1.4.5.8,数据加密,1,供给,5
|
||||||
|
1.4.2.3,工控漏洞扫描,1,供给,5
|
||||||
|
2.1.4.2.2,数据安全管理,2.1.4.2,工业大数据管理,5
|
||||||
|
2.1.4.2.1,数据质量管理,2.1.4.2,工业大数据管理,5
|
||||||
|
1.3,工业软件,1,供给,4
|
||||||
|
2.1.4.1.4,时序数据库,2.1.4.1,工业大数据存储,4
|
||||||
|
2.3,边缘层,2,工业互联网平台,3
|
||||||
|
2.2,IaaS,2,工业互联网平台,3
|
||||||
|
2.1.4.1.1,关系型数据库,2.1.4.1,工业大数据存储,3
|
||||||
|
2.1.4.1.2,分布式数据库,2.1.4.1,工业大数据存储,3
|
||||||
|
2.1.4.1.3,实时数据库,2.1.4.1,工业大数据存储,3
|
||||||
|
2.1.4.2,工业大数据管理,2.1.4,工业大数据,3
|
||||||
|
1.3.1.3,计算机辅助制造CAM,1.3.1,设计研发,2
|
||||||
|
1.3.2,采购供应,1,供给,2
|
||||||
|
1.3.3,生产制造,1.3,工业软件,1
|
||||||
|
2.3.3,协议转换,2,工业互联网平台,1
|
||||||
|
1.3.4.3,人力资源管理HRM,1.3.4,企业运营管理,1
|
||||||
|
2.1.4.1,工业大数据存储,2.1.4,工业大数据,1
|
||||||
|
1.3.3.7,故障预测与健康管理PHM,1.3.3,生产制造,1
|
||||||
|
1.3.4,企业运营管理,1.3,工业软件,1
|
||||||
|
1.3.5,仓储物流,1,供给,1
|
||||||
|
1.4.4.1,身份鉴别与访问控制,1.4.4,平台安全,1
|
||||||
|
1.3.2.1,供应链管理SCM,1,供给,1
|
|
Before Width: | Height: | Size: 649 KiB After Width: | Height: | Size: 649 KiB |
|
@ -0,0 +1,144 @@
|
||||||
|
id_firm,Name,count
|
||||||
|
126,华为,468
|
||||||
|
142,深信服,300
|
||||||
|
41,启明星辰,200
|
||||||
|
53,天融信,150
|
||||||
|
106,阿里巴巴,146
|
||||||
|
170,Pseudo1,125
|
||||||
|
99,Siemens,120
|
||||||
|
79,PTC,117
|
||||||
|
130,金蝶,91
|
||||||
|
13,东方国信,80
|
||||||
|
135,浪潮,73
|
||||||
|
23,和利时,71
|
||||||
|
58,用友,62
|
||||||
|
97,General Electric,54
|
||||||
|
29,京东工业品,52
|
||||||
|
63,长扬科技,50
|
||||||
|
85,Dassault,50
|
||||||
|
157,新华三,50
|
||||||
|
140,山石网科,50
|
||||||
|
148,腾讯,49
|
||||||
|
102,Amazon AWS,47
|
||||||
|
22,航天云网,46
|
||||||
|
40,奇安信,39
|
||||||
|
0,360科技,38
|
||||||
|
98,Microsoft Azure,38
|
||||||
|
84,Bosch,35
|
||||||
|
81,SAP,35
|
||||||
|
74,HoneyWell,32
|
||||||
|
100,Synopsys,29
|
||||||
|
86,Dell EMC,28
|
||||||
|
80,Salesforce,28
|
||||||
|
108,百度,25
|
||||||
|
105,Intel,25
|
||||||
|
49,数码大方,24
|
||||||
|
47,首自信,24
|
||||||
|
95,Schneider,22
|
||||||
|
39,Autodesk,21
|
||||||
|
168,中控技术,20
|
||||||
|
6,安世亚太,20
|
||||||
|
16,东土科技,20
|
||||||
|
94,Mitsubishi,19
|
||||||
|
75,IBM,19
|
||||||
|
73,FANUC,18
|
||||||
|
124,海尔,18
|
||||||
|
117,格创东智,17
|
||||||
|
26,寄云科技,17
|
||||||
|
155,小米,17
|
||||||
|
159,徐工集团,16
|
||||||
|
57,亚控科技,13
|
||||||
|
149,天泽智云,13
|
||||||
|
93,Cadence,13
|
||||||
|
62,云道智造,13
|
||||||
|
82,Uptake,12
|
||||||
|
78,OutSystems,12
|
||||||
|
161,研华科技,12
|
||||||
|
60,宇动源,11
|
||||||
|
165,智能云科,11
|
||||||
|
33,蓝谷信息,10
|
||||||
|
42,山大华天,10
|
||||||
|
67,中国移动,10
|
||||||
|
131,九物互联,10
|
||||||
|
38,牛刀,10
|
||||||
|
103,STMicroelectronics ,9
|
||||||
|
144,树根互联,9
|
||||||
|
56,芯愿景,8
|
||||||
|
143,沈阳自动化研究所,8
|
||||||
|
127,华为海思,8
|
||||||
|
153,武汉开目,8
|
||||||
|
3,艾克斯特,7
|
||||||
|
45,石化盈科,7
|
||||||
|
68,中望软件,7
|
||||||
|
31,昆仑数据,6
|
||||||
|
46,适创科技,6
|
||||||
|
111,鼎捷软件,6
|
||||||
|
89,Rockwell,6
|
||||||
|
150,唯捷创芯,6
|
||||||
|
169,中芯国际,6
|
||||||
|
69,紫光集团,5
|
||||||
|
113,飞腾信息,5
|
||||||
|
167,中环股份,5
|
||||||
|
129,华中数控,5
|
||||||
|
43,神舟软件,5
|
||||||
|
71,Altair,4
|
||||||
|
104,Infineon,4
|
||||||
|
77,Oracle,4
|
||||||
|
123,海得控制,4
|
||||||
|
145,思普软件,4
|
||||||
|
35,凌昊智能,4
|
||||||
|
163,优也科技,4
|
||||||
|
24,华大电子,4
|
||||||
|
32,兰光创新,4
|
||||||
|
115,富士康,4
|
||||||
|
147,拓邦股份,4
|
||||||
|
9,北京航天测控,3
|
||||||
|
88,HPE,3
|
||||||
|
87,Texas Instruments,3
|
||||||
|
120,广州数控,3
|
||||||
|
12,大唐软件,3
|
||||||
|
64,中电智科,3
|
||||||
|
90,Mentor Graphics,3
|
||||||
|
101,Analog Devices,3
|
||||||
|
116,概伦电子,3
|
||||||
|
166,中国电子科技网络信息安全,3
|
||||||
|
119,广联达,3
|
||||||
|
70,ABB,3
|
||||||
|
20,海基科技,3
|
||||||
|
65,中国电信,3
|
||||||
|
72,ANSYS,3
|
||||||
|
4,爱创科技,3
|
||||||
|
36,龙芯中科,3
|
||||||
|
44,圣邦微电子,3
|
||||||
|
146,苏州浩辰,3
|
||||||
|
14,东华软件,3
|
||||||
|
83,Emerson,2
|
||||||
|
138,启明信息,2
|
||||||
|
10,北京英贝思,2
|
||||||
|
128,华伍股份,2
|
||||||
|
15,东软集团,2
|
||||||
|
154,西格数据,2
|
||||||
|
156,芯禾科技,2
|
||||||
|
48,曙光信息,2
|
||||||
|
50,索为系统,2
|
||||||
|
141,上海新华控制,2
|
||||||
|
61,元年科技,2
|
||||||
|
164,震坤行,2
|
||||||
|
2,706所,2
|
||||||
|
134,朗坤智慧,2
|
||||||
|
137,美林数据,2
|
||||||
|
25,华大九天,2
|
||||||
|
34,力控科技,2
|
||||||
|
132,科远智慧,1
|
||||||
|
92,Omron,1
|
||||||
|
21,Hexagon,1
|
||||||
|
96,Cisco,1
|
||||||
|
18,国能智深,1
|
||||||
|
118,工邦邦,1
|
||||||
|
91,Moxa,1
|
||||||
|
125,华数机器人,1
|
||||||
|
133,蓝盾股份,1
|
||||||
|
109,宝信软件,1
|
||||||
|
139,容知日新,1
|
||||||
|
66,中国联通,1
|
||||||
|
1,51WORLD,1
|
|
|
@ -0,0 +1,358 @@
|
||||||
|
id_firm,name_firm,id_product,name_product,count
|
||||||
|
126,华为,1.4,工业互联网安全,385
|
||||||
|
142,深信服,1.4.3,网络安全,150
|
||||||
|
41,启明星辰,1.4.5,数据安全,150
|
||||||
|
142,深信服,1.4.2,控制安全,150
|
||||||
|
170,Pseudo1,1,供给,125
|
||||||
|
106,阿里巴巴,1.3,工业软件,67
|
||||||
|
29,京东工业品,1.3,工业软件,52
|
||||||
|
53,天融信,1.4.2.3,工控漏洞扫描,50
|
||||||
|
41,启明星辰,1.4.3.2,流量检测,50
|
||||||
|
23,和利时,1.4.2.7,工控原生安全,50
|
||||||
|
63,长扬科技,1.4.4.5,安全态势感知,50
|
||||||
|
157,新华三,1.4.1,设备安全,50
|
||||||
|
53,天融信,1.4.5.8,数据加密,50
|
||||||
|
140,山石网科,1.4.5.1,恶意代码检测系统,50
|
||||||
|
135,浪潮,1.3.2.1,供应链管理SCM,50
|
||||||
|
130,金蝶,1.3.5,仓储物流,50
|
||||||
|
99,Siemens,2.1,PaaS,50
|
||||||
|
53,天融信,1.4.3.6,沙箱类设备,50
|
||||||
|
102,Amazon AWS,2,工业互联网平台,45
|
||||||
|
130,金蝶,1.3.2,采购供应,40
|
||||||
|
40,奇安信,1.4.4,平台安全,39
|
||||||
|
0,360科技,1.4.4,平台安全,38
|
||||||
|
98,Microsoft Azure,2,工业互联网平台,38
|
||||||
|
58,用友,1.3.2,采购供应,36
|
||||||
|
148,腾讯,2.1.3,工业物联网,32
|
||||||
|
74,HoneyWell,2.1.3,工业物联网,30
|
||||||
|
100,Synopsys,1.3.1,设计研发,29
|
||||||
|
85,Dassault,1.3.1,设计研发,29
|
||||||
|
86,Dell EMC,1.1,工业自动化,28
|
||||||
|
99,Siemens,1.3.1,设计研发,27
|
||||||
|
97,General Electric,2.1.3,工业物联网,27
|
||||||
|
106,阿里巴巴,2.1.3,工业物联网,27
|
||||||
|
126,华为,2.1.3,工业物联网,26
|
||||||
|
105,Intel,1.1,工业自动化,25
|
||||||
|
80,Salesforce,2.1.1,开发工具,25
|
||||||
|
79,PTC,2.1.2,工业模型库,25
|
||||||
|
108,百度,2.1.3,工业物联网,24
|
||||||
|
84,Bosch,2.1.2,工业模型库,22
|
||||||
|
58,用友,2.1.2,工业模型库,22
|
||||||
|
39,Autodesk,1.3.1,设计研发,21
|
||||||
|
97,General Electric,1.3.3,生产制造,21
|
||||||
|
106,阿里巴巴,1.1,工业自动化,21
|
||||||
|
85,Dassault,2.1.1,开发工具,21
|
||||||
|
126,华为,1.1,工业自动化,21
|
||||||
|
99,Siemens,1.3.3,生产制造,20
|
||||||
|
99,Siemens,2.3,边缘层,20
|
||||||
|
106,阿里巴巴,2.1.1,开发工具,19
|
||||||
|
126,华为,2.3,边缘层,19
|
||||||
|
75,IBM,1.3.3,生产制造,19
|
||||||
|
94,Mitsubishi,1.1,工业自动化,19
|
||||||
|
73,FANUC,2.1.3,工业物联网,18
|
||||||
|
81,SAP,2.1.2,工业模型库,18
|
||||||
|
95,Schneider,2.3,边缘层,18
|
||||||
|
155,小米,2.3,边缘层,17
|
||||||
|
148,腾讯,2.1.1,开发工具,17
|
||||||
|
124,海尔,2.3,边缘层,16
|
||||||
|
159,徐工集团,2.1.2,工业模型库,16
|
||||||
|
126,华为,1.2,工业互联网网络,15
|
||||||
|
93,Cadence,1.3.1,设计研发,13
|
||||||
|
106,阿里巴巴,1.2,工业互联网网络,12
|
||||||
|
84,Bosch,2.3,边缘层,12
|
||||||
|
13,东方国信,2.1.3.7,制造类API,11
|
||||||
|
13,东方国信,2.1.3.4,应用管理服务,11
|
||||||
|
13,东方国信,2.1.3.5,容器服务,10
|
||||||
|
79,PTC,2.1.3.2,平台基础服务,10
|
||||||
|
67,中国移动,1.2,工业互联网网络,10
|
||||||
|
79,PTC,2.1.3.1,物联网服务,9
|
||||||
|
79,PTC,2.1.3.4,应用管理服务,9
|
||||||
|
103,STMicroelectronics ,1.1.1,工业计算芯片,9
|
||||||
|
13,东方国信,2.1.3.1,物联网服务,9
|
||||||
|
13,东方国信,2.1.3.3,工业引擎服务,8
|
||||||
|
79,PTC,2.1.3.5,容器服务,8
|
||||||
|
79,PTC,2.1.4.1,工业大数据存储,7
|
||||||
|
13,东方国信,2.1.3.6,微服务,7
|
||||||
|
79,PTC,2.1.3.7,制造类API,7
|
||||||
|
81,SAP,2.1.4.1,工业大数据存储,7
|
||||||
|
81,SAP,2.1.4.2,工业大数据管理,7
|
||||||
|
79,PTC,2.1.3.6,微服务,7
|
||||||
|
79,PTC,2.3.3,协议转换,6
|
||||||
|
79,PTC,2.1.3.3,工业引擎服务,6
|
||||||
|
16,东土科技,2.3.1,工业数据接入,6
|
||||||
|
150,唯捷创芯,1.1.1,工业计算芯片,6
|
||||||
|
49,数码大方,1.3.1.1,计算机辅助设计CAD,6
|
||||||
|
79,PTC,2.3.1,工业数据接入,6
|
||||||
|
47,首自信,2.1.3.6,微服务,6
|
||||||
|
56,芯愿景,1.1.1,工业计算芯片,6
|
||||||
|
169,中芯国际,1.1.1,工业计算芯片,6
|
||||||
|
97,General Electric,1.2,工业互联网网络,6
|
||||||
|
46,适创科技,1.3.1.2,计算机辅助工程CAE,6
|
||||||
|
47,首自信,2.1.2.1,数据算法模型,6
|
||||||
|
13,东方国信,2.1.3.2,平台基础服务,6
|
||||||
|
16,东土科技,1.1.3,工业服务器,5
|
||||||
|
161,研华科技,2.3.3,协议转换,5
|
||||||
|
16,东土科技,2.3.3,协议转换,5
|
||||||
|
22,航天云网,2.1.3.6,微服务,5
|
||||||
|
168,中控技术,2.3.3,协议转换,5
|
||||||
|
13,东方国信,2.3.2,边缘数据处理,5
|
||||||
|
22,航天云网,2.3.1,工业数据接入,5
|
||||||
|
153,武汉开目,1.3.1.1,计算机辅助设计CAD,5
|
||||||
|
69,紫光集团,1.1.1,工业计算芯片,5
|
||||||
|
22,航天云网,2.3.3,协议转换,5
|
||||||
|
127,华为海思,1.1.1,工业计算芯片,5
|
||||||
|
6,安世亚太,2.1.2.1,数据算法模型,5
|
||||||
|
79,PTC,2.1.4.2,工业大数据管理,5
|
||||||
|
23,和利时,2.3.3,协议转换,5
|
||||||
|
42,山大华天,1.3.1.1,计算机辅助设计CAD,5
|
||||||
|
113,飞腾信息,1.1.1,工业计算芯片,5
|
||||||
|
167,中环股份,1.1.1,工业计算芯片,5
|
||||||
|
78,OutSystems,2.1.1.5,数字孪生建模工具,4
|
||||||
|
32,兰光创新,1.2.3,数据互通,4
|
||||||
|
68,中望软件,1.3.1.2,计算机辅助工程CAE,4
|
||||||
|
78,OutSystems,2.1.1.2,低代码开发工具,4
|
||||||
|
6,安世亚太,2.1.2.4,行业机理模型,4
|
||||||
|
165,智能云科,2.1.2.2,业务流程模型,4
|
||||||
|
24,华大电子,1.1.1,工业计算芯片,4
|
||||||
|
62,云道智造,2.1.2.2,业务流程模型,4
|
||||||
|
23,和利时,2.3.2,边缘数据处理,4
|
||||||
|
16,东土科技,2.3.2,边缘数据处理,4
|
||||||
|
6,安世亚太,2.1.2.3,研发仿真模型,4
|
||||||
|
22,航天云网,2.1.3.4,应用管理服务,4
|
||||||
|
71,Altair,1.3.1.2,计算机辅助工程CAE,4
|
||||||
|
161,研华科技,2.3.2,边缘数据处理,4
|
||||||
|
168,中控技术,2.3.2,边缘数据处理,4
|
||||||
|
35,凌昊智能,1.1.3,工业服务器,4
|
||||||
|
33,蓝谷信息,2.1.2.4,行业机理模型,4
|
||||||
|
57,亚控科技,2.3.3,协议转换,4
|
||||||
|
129,华中数控,1.1.2,工业控制器,4
|
||||||
|
13,东方国信,2.3.1,工业数据接入,4
|
||||||
|
104,Infineon,1.1.1,工业计算芯片,4
|
||||||
|
131,九物互联,2.1.1.2,低代码开发工具,4
|
||||||
|
95,Schneider,1.2.3,数据互通,4
|
||||||
|
149,天泽智云,2.1.2.4,行业机理模型,4
|
||||||
|
42,山大华天,1.3.1.4,计算机辅助工艺过程设计CAPP,4
|
||||||
|
135,浪潮,2.1.3.7,制造类API,4
|
||||||
|
117,格创东智,2.1.1.4,组态建模工具,4
|
||||||
|
82,Uptake,2.1.2.4,行业机理模型,4
|
||||||
|
57,亚控科技,2.3.2,边缘数据处理,4
|
||||||
|
43,神舟软件,1.3.1.6,产品生命周期管理PLM,4
|
||||||
|
145,思普软件,1.3.1.4,计算机辅助工艺过程设计CAPP,4
|
||||||
|
123,海得控制,1.1.2,工业控制器,4
|
||||||
|
38,牛刀,2.1.1.5,数字孪生建模工具,4
|
||||||
|
149,天泽智云,2.1.2.3,研发仿真模型,4
|
||||||
|
147,拓邦股份,1.1.2,工业控制器,4
|
||||||
|
6,安世亚太,2.1.2.2,业务流程模型,4
|
||||||
|
4,爱创科技,1.2.2,标识解析,3
|
||||||
|
36,龙芯中科,1.1.1,工业计算芯片,3
|
||||||
|
33,蓝谷信息,2.1.2.2,业务流程模型,3
|
||||||
|
115,富士康,1.1.3,工业服务器,3
|
||||||
|
49,数码大方,2.1.2.1,数据算法模型,3
|
||||||
|
49,数码大方,1.3.3.1,制造执行系统MES,3
|
||||||
|
23,和利时,2.1.3.6,微服务,3
|
||||||
|
49,数码大方,2.1.2.2,业务流程模型,3
|
||||||
|
64,中电智科,1.1.2,工业控制器,3
|
||||||
|
49,数码大方,1.3.1.6,产品生命周期管理PLM,3
|
||||||
|
49,数码大方,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
||||||
|
47,首自信,2.1.2.4,行业机理模型,3
|
||||||
|
47,首自信,2.1.1.2,低代码开发工具,3
|
||||||
|
62,云道智造,2.1.2.4,行业机理模型,3
|
||||||
|
117,格创东智,2.1.1.2,低代码开发工具,3
|
||||||
|
60,宇动源,2.1.1.1,算法建模工具,3
|
||||||
|
26,寄云科技,2.1.3.1,物联网服务,3
|
||||||
|
117,格创东智,2.1.1.1,算法建模工具,3
|
||||||
|
26,寄云科技,2.1.3.3,工业引擎服务,3
|
||||||
|
44,圣邦微电子,1.1.1,工业计算芯片,3
|
||||||
|
62,云道智造,1.3.1.2,计算机辅助工程CAE,3
|
||||||
|
26,寄云科技,2.1.3.6,微服务,3
|
||||||
|
6,安世亚太,1.3.1.2,计算机辅助工程CAE,3
|
||||||
|
57,亚控科技,2.3.1,工业数据接入,3
|
||||||
|
3,艾克斯特,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
||||||
|
116,概伦电子,1.3.1.7,电子设计自动化EDA,3
|
||||||
|
3,艾克斯特,1.3.1.6,产品生命周期管理PLM,3
|
||||||
|
31,昆仑数据,1.3.3.3,数据采集与监视控制系统SCADA,3
|
||||||
|
60,宇动源,2.1.1.2,低代码开发工具,3
|
||||||
|
65,中国电信,1.2.1,网络互联,3
|
||||||
|
23,和利时,2.3.1,工业数据接入,3
|
||||||
|
68,中望软件,1.3.1.1,计算机辅助设计CAD,3
|
||||||
|
87,Texas Instruments,1.1.1,工业计算芯片,3
|
||||||
|
149,天泽智云,2.1.2.2,业务流程模型,3
|
||||||
|
120,广州数控,1.2.3,数据互通,3
|
||||||
|
146,苏州浩辰,1.3.1.1,计算机辅助设计CAD,3
|
||||||
|
144,树根互联,2.1.2.4,行业机理模型,3
|
||||||
|
22,航天云网,2.1.3.7,制造类API,3
|
||||||
|
80,Salesforce,1.3.4,企业运营管理,3
|
||||||
|
81,SAP,1.3.4,企业运营管理,3
|
||||||
|
82,Uptake,2.1.2.1,数据算法模型,3
|
||||||
|
82,Uptake,2.1.2.2,业务流程模型,3
|
||||||
|
111,鼎捷软件,1.3.1.6,产品生命周期管理PLM,3
|
||||||
|
135,浪潮,2.1.3.4,应用管理服务,3
|
||||||
|
12,大唐软件,1.2.1,网络互联,3
|
||||||
|
135,浪潮,2.1.3.3,工业引擎服务,3
|
||||||
|
88,HPE,1.1.3,工业服务器,3
|
||||||
|
89,Rockwell,1.1.2,工业控制器,3
|
||||||
|
9,北京航天测控,1.3.3.6,运维保障系统MRO,3
|
||||||
|
135,浪潮,1.1.3,工业服务器,3
|
||||||
|
90,Mentor Graphics,1.3.1.7,电子设计自动化EDA,3
|
||||||
|
131,九物互联,2.1.1.4,组态建模工具,3
|
||||||
|
13,东方国信,1.2.2,标识解析,3
|
||||||
|
101,Analog Devices,1.1.1,工业计算芯片,3
|
||||||
|
127,华为海思,1.1.3,工业服务器,3
|
||||||
|
153,武汉开目,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
||||||
|
79,PTC,2.3.2,边缘数据处理,3
|
||||||
|
161,研华科技,2.3.1,工业数据接入,3
|
||||||
|
168,中控技术,1.3.3.2,分布式控制系统DCS,3
|
||||||
|
22,航天云网,2.1.3.3,工业引擎服务,3
|
||||||
|
72,ANSYS,1.3.1.2,计算机辅助工程CAE,3
|
||||||
|
22,航天云网,1.2.2,标识解析,3
|
||||||
|
20,海基科技,1.3.1.2,计算机辅助工程CAE,3
|
||||||
|
119,广联达,1.3.1.1,计算机辅助设计CAD,3
|
||||||
|
168,中控技术,2.3.1,工业数据接入,3
|
||||||
|
79,PTC,1.3.1.4,计算机辅助工艺过程设计CAPP,3
|
||||||
|
165,智能云科,2.1.2.1,数据算法模型,3
|
||||||
|
79,PTC,1.3.1.6,产品生命周期管理PLM,3
|
||||||
|
79,PTC,1.3.1.1,计算机辅助设计CAD,3
|
||||||
|
166,中国电子科技网络信息安全,1.2.3,数据互通,3
|
||||||
|
165,智能云科,2.1.2.4,行业机理模型,3
|
||||||
|
58,用友,1.3.1.6,产品生命周期管理PLM,2
|
||||||
|
117,格创东智,2.1.1.3,流程开发工具,2
|
||||||
|
70,ABB,1.3.3.2,分布式控制系统DCS,2
|
||||||
|
10,北京英贝思,1.3.3.5,企业资产管理系统EAM,2
|
||||||
|
102,Amazon AWS,2.1.4,工业大数据,2
|
||||||
|
99,Siemens,1.1.2,工业控制器,2
|
||||||
|
74,HoneyWell,1.3.3.2,分布式控制系统DCS,2
|
||||||
|
77,Oracle,1.3.3.6,运维保障系统MRO,2
|
||||||
|
77,Oracle,1.3.4,企业运营管理,2
|
||||||
|
49,数码大方,2.1.2.4,行业机理模型,2
|
||||||
|
50,索为系统,1.3.1.5,产品数据管理PDM,2
|
||||||
|
89,Rockwell,1.2.1,网络互联,2
|
||||||
|
58,用友,1.2.2,标识解析,2
|
||||||
|
78,OutSystems,2.1.1.1,算法建模工具,2
|
||||||
|
56,芯愿景,1.3.1.7,电子设计自动化EDA,2
|
||||||
|
111,鼎捷软件,1.3.4.1,企业资源计划ERP,2
|
||||||
|
57,亚控科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
||||||
|
78,OutSystems,2.1.1.3,流程开发工具,2
|
||||||
|
61,元年科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
||||||
|
83,Emerson,1.3.3.2,分布式控制系统DCS,2
|
||||||
|
82,Uptake,2.1.2.3,研发仿真模型,2
|
||||||
|
60,宇动源,2.1.1.5,数字孪生建模工具,2
|
||||||
|
60,宇动源,2.1.1.4,组态建模工具,2
|
||||||
|
62,云道智造,2.1.2.1,数据算法模型,2
|
||||||
|
33,蓝谷信息,2.1.2.3,研发仿真模型,2
|
||||||
|
48,曙光信息,1.2.2,标识解析,2
|
||||||
|
22,航天云网,1.3.3.6,运维保障系统MRO,2
|
||||||
|
26,寄云科技,2.1.3.2,平台基础服务,2
|
||||||
|
144,树根互联,2.1.2.2,业务流程模型,2
|
||||||
|
25,华大九天,1.3.1.7,电子设计自动化EDA,2
|
||||||
|
23,和利时,1.3.3.3,数据采集与监视控制系统SCADA,2
|
||||||
|
138,启明信息,1.3.1.5,产品数据管理PDM,2
|
||||||
|
23,和利时,1.3.3.1,制造执行系统MES,2
|
||||||
|
22,航天云网,2.3.2,边缘数据处理,2
|
||||||
|
22,航天云网,2.1.3.5,容器服务,2
|
||||||
|
14,东华软件,1.3.3.4,可编程逻揖控制系统PLC,2
|
||||||
|
22,航天云网,2.1.3.1,物联网服务,2
|
||||||
|
22,航天云网,2.1.1.5,数字孪生建模工具,2
|
||||||
|
22,航天云网,2.1.1.3,流程开发工具,2
|
||||||
|
22,航天云网,2.1.1.2,低代码开发工具,2
|
||||||
|
22,航天云网,2.1.1.1,算法建模工具,2
|
||||||
|
141,上海新华控制,1.3.3.2,分布式控制系统DCS,2
|
||||||
|
26,寄云科技,2.1.3.5,容器服务,2
|
||||||
|
2,706所,1.1.3,工业服务器,2
|
||||||
|
124,海尔,1.2.1,网络互联,2
|
||||||
|
168,中控技术,1.3.3.4,可编程逻揖控制系统PLC,2
|
||||||
|
143,沈阳自动化研究所,2.1.1.2,低代码开发工具,2
|
||||||
|
168,中控技术,1.1.2,工业控制器,2
|
||||||
|
143,沈阳自动化研究所,2.1.1.3,流程开发工具,2
|
||||||
|
164,震坤行,1.3.3.6,运维保障系统MRO,2
|
||||||
|
163,优也科技,2.1.4.2.2,数据安全管理,2
|
||||||
|
143,沈阳自动化研究所,2.1.1.4,组态建模工具,2
|
||||||
|
156,芯禾科技,1.3.1.7,电子设计自动化EDA,2
|
||||||
|
143,沈阳自动化研究所,2.1.1.5,数字孪生建模工具,2
|
||||||
|
144,树根互联,2.1.2.1,数据算法模型,2
|
||||||
|
15,东软集团,1.3.3.5,企业资产管理系统EAM,2
|
||||||
|
149,天泽智云,2.1.2.1,数据算法模型,2
|
||||||
|
26,寄云科技,2.1.3.4,应用管理服务,2
|
||||||
|
144,树根互联,2.1.2.3,研发仿真模型,2
|
||||||
|
26,寄云科技,2.1.3.7,制造类API,2
|
||||||
|
135,浪潮,2.1.3.1,物联网服务,2
|
||||||
|
117,格创东智,2.1.1.5,数字孪生建模工具,2
|
||||||
|
134,朗坤智慧,1.3.3.5,企业资产管理系统EAM,2
|
||||||
|
13,东方国信,2.3.3,协议转换,2
|
||||||
|
38,牛刀,2.1.1.2,低代码开发工具,2
|
||||||
|
38,牛刀,2.1.1.1,算法建模工具,2
|
||||||
|
13,东方国信,2.1.4.1.4,时序数据库,2
|
||||||
|
34,力控科技,1.3.3.3,数据采集与监视控制系统SCADA,2
|
||||||
|
135,浪潮,2.1.3.2,平台基础服务,2
|
||||||
|
128,华伍股份,1.1.2,工业控制器,2
|
||||||
|
47,首自信,2.1.2.2,业务流程模型,2
|
||||||
|
135,浪潮,2.1.3.5,容器服务,2
|
||||||
|
135,浪潮,2.1.3.6,微服务,2
|
||||||
|
131,九物互联,2.1.1.1,算法建模工具,2
|
||||||
|
99,Siemens,1.2.1,网络互联,1
|
||||||
|
13,东方国信,2.1.4.1.2,分布式数据库,1
|
||||||
|
131,九物互联,2.1.1.3,流程开发工具,1
|
||||||
|
111,鼎捷软件,1.3.3.1,制造执行系统MES,1
|
||||||
|
129,华中数控,1.2.3,数据互通,1
|
||||||
|
13,东方国信,2.1.4.2.1,数据质量管理,1
|
||||||
|
126,华为,2.1.1.5,数字孪生建模工具,1
|
||||||
|
130,金蝶,1.3.4.1,企业资源计划ERP,1
|
||||||
|
96,Cisco,1.2.3,数据互通,1
|
||||||
|
91,Moxa,1.2.1,网络互联,1
|
||||||
|
132,科远智慧,1.3.3.2,分布式控制系统DCS,1
|
||||||
|
133,蓝盾股份,1.4.4.1,身份鉴别与访问控制,1
|
||||||
|
92,Omron,1.3.3.4,可编程逻揖控制系统PLC,1
|
||||||
|
108,百度,2.2,IaaS,1
|
||||||
|
14,东华软件,1.3.4.3,人力资源管理HRM,1
|
||||||
|
125,华数机器人,1.2.3,数据互通,1
|
||||||
|
139,容知日新,1.3.3.7,故障预测与健康管理PHM,1
|
||||||
|
89,Rockwell,1.3.3.1,制造执行系统MES,1
|
||||||
|
135,浪潮,1.3.4.1,企业资源计划ERP,1
|
||||||
|
137,美林数据,2.1.4.2.1,数据质量管理,1
|
||||||
|
137,美林数据,2.1.4.1.3,实时数据库,1
|
||||||
|
84,Bosch,2.1.4,工业大数据,1
|
||||||
|
135,浪潮,2.2,IaaS,1
|
||||||
|
109,宝信软件,1.3.3.1,制造执行系统MES,1
|
||||||
|
18,国能智深,1.3.3.2,分布式控制系统DCS,1
|
||||||
|
154,西格数据,2.1.4.1.2,分布式数据库,1
|
||||||
|
45,石化盈科,1.3.4.1,企业资源计划ERP,1
|
||||||
|
115,富士康,2.1.4,工业大数据,1
|
||||||
|
38,牛刀,2.1.1.3,流程开发工具,1
|
||||||
|
38,牛刀,2.1.1.4,组态建模工具,1
|
||||||
|
117,格创东智,2.1.4.2.1,数据质量管理,1
|
||||||
|
117,格创东智,2.1.4.1.1,关系型数据库,1
|
||||||
|
42,山大华天,1.3.1.3,计算机辅助制造CAM,1
|
||||||
|
43,神舟软件,1.3.1.5,产品数据管理PDM,1
|
||||||
|
45,石化盈科,1.3.3.1,制造执行系统MES,1
|
||||||
|
45,石化盈科,2.1.4.1.2,分布式数据库,1
|
||||||
|
31,昆仑数据,2.1.4.2.1,数据质量管理,1
|
||||||
|
45,石化盈科,2.1.4.1.3,实时数据库,1
|
||||||
|
45,石化盈科,2.1.4.1.4,时序数据库,1
|
||||||
|
45,石化盈科,2.1.4.2.1,数据质量管理,1
|
||||||
|
45,石化盈科,2.1.4.2.2,数据安全管理,1
|
||||||
|
49,数码大方,2.1.2.3,研发仿真模型,1
|
||||||
|
47,首自信,2.1.1.1,算法建模工具,1
|
||||||
|
47,首自信,2.1.1.3,流程开发工具,1
|
||||||
|
47,首自信,2.1.1.4,组态建模工具,1
|
||||||
|
33,蓝谷信息,2.1.2.1,数据算法模型,1
|
||||||
|
31,昆仑数据,2.1.4.1.3,实时数据库,1
|
||||||
|
154,西格数据,2.1.4.2.2,数据安全管理,1
|
||||||
|
70,ABB,1.3.3.4,可编程逻揖控制系统PLC,1
|
||||||
|
163,优也科技,2.1.4.1.1,关系型数据库,1
|
||||||
|
163,优也科技,2.1.4.1.4,时序数据库,1
|
||||||
|
165,智能云科,2.1.2.3,研发仿真模型,1
|
||||||
|
168,中控技术,1.3.3.1,制造执行系统MES,1
|
||||||
|
47,首自信,2.1.2.3,研发仿真模型,1
|
||||||
|
21,Hexagon,1.3.1.3,计算机辅助制造CAM,1
|
||||||
|
22,航天云网,2.1.1.4,组态建模工具,1
|
||||||
|
22,航天云网,2.1.3.2,平台基础服务,1
|
||||||
|
23,和利时,1.3.3.2,分布式控制系统DCS,1
|
||||||
|
31,昆仑数据,2.1.4.1.1,关系型数据库,1
|
||||||
|
66,中国联通,1.2.1,网络互联,1
|
||||||
|
23,和利时,1.3.3.4,可编程逻揖控制系统PLC,1
|
||||||
|
118,工邦邦,1.3.3.6,运维保障系统MRO,1
|
||||||
|
1,51WORLD,2.1.1.5,数字孪生建模工具,1
|
||||||
|
62,云道智造,2.1.2.3,研发仿真模型,1
|
||||||
|
117,格创东智,2.1.4.2.2,数据安全管理,1
|
||||||
|
3,艾克斯特,1.3.4.1,企业资源计划ERP,1
|
||||||
|
60,宇动源,2.1.1.3,流程开发工具,1
|
||||||
|
126,华为,2.2,IaaS,1
|
|
|
@ -0,0 +1,82 @@
|
||||||
|
id_product,Name,count
|
||||||
|
1.4,工业互联网安全,385
|
||||||
|
2.1.3,工业物联网,184
|
||||||
|
1.4.5,数据安全,150
|
||||||
|
1.4.3,网络安全,150
|
||||||
|
1.4.2,控制安全,150
|
||||||
|
1,供给,125
|
||||||
|
1.3,工业软件,119
|
||||||
|
1.3.1,设计研发,119
|
||||||
|
1.1,工业自动化,114
|
||||||
|
2.1.2,工业模型库,103
|
||||||
|
2.3,边缘层,102
|
||||||
|
2,工业互联网平台,83
|
||||||
|
2.1.1,开发工具,82
|
||||||
|
1.4.4,平台安全,77
|
||||||
|
1.3.2,采购供应,76
|
||||||
|
1.1.1,工业计算芯片,67
|
||||||
|
1.3.3,生产制造,60
|
||||||
|
2.1,PaaS,50
|
||||||
|
1.3.5,仓储物流,50
|
||||||
|
1.3.2.1,供应链管理SCM,50
|
||||||
|
1.4.5.8,数据加密,50
|
||||||
|
1.4.5.1,恶意代码检测系统,50
|
||||||
|
1.4.4.5,安全态势感知,50
|
||||||
|
1.4.3.6,沙箱类设备,50
|
||||||
|
1.4.3.2,流量检测,50
|
||||||
|
1.4.2.7,工控原生安全,50
|
||||||
|
1.4.2.3,工控漏洞扫描,50
|
||||||
|
1.4.1,设备安全,50
|
||||||
|
1.2,工业互联网网络,43
|
||||||
|
2.3.3,协议转换,37
|
||||||
|
2.3.1,工业数据接入,33
|
||||||
|
2.1.3.6,微服务,33
|
||||||
|
2.3.2,边缘数据处理,30
|
||||||
|
2.1.2.4,行业机理模型,30
|
||||||
|
2.1.3.4,应用管理服务,29
|
||||||
|
1.3.1.1,计算机辅助设计CAD,28
|
||||||
|
2.1.2.2,业务流程模型,28
|
||||||
|
2.1.2.1,数据算法模型,27
|
||||||
|
2.1.3.7,制造类API,27
|
||||||
|
1.3.1.2,计算机辅助工程CAE,26
|
||||||
|
2.1.3.1,物联网服务,25
|
||||||
|
1.1.2,工业控制器,24
|
||||||
|
2.1.3.5,容器服务,24
|
||||||
|
2.1.3.3,工业引擎服务,23
|
||||||
|
2.1.1.2,低代码开发工具,23
|
||||||
|
1.1.3,工业服务器,23
|
||||||
|
2.1.3.2,平台基础服务,21
|
||||||
|
1.3.1.4,计算机辅助工艺过程设计CAPP,20
|
||||||
|
2.1.2.3,研发仿真模型,18
|
||||||
|
2.1.1.5,数字孪生建模工具,18
|
||||||
|
1.3.1.6,产品生命周期管理PLM,18
|
||||||
|
1.2.3,数据互通,17
|
||||||
|
2.1.1.1,算法建模工具,15
|
||||||
|
2.1.1.4,组态建模工具,14
|
||||||
|
2.1.4.1,工业大数据存储,14
|
||||||
|
1.3.3.2,分布式控制系统DCS,14
|
||||||
|
1.2.2,标识解析,13
|
||||||
|
1.2.1,网络互联,13
|
||||||
|
2.1.4.2,工业大数据管理,12
|
||||||
|
1.3.1.7,电子设计自动化EDA,12
|
||||||
|
2.1.1.3,流程开发工具,12
|
||||||
|
1.3.3.3,数据采集与监视控制系统SCADA,11
|
||||||
|
1.3.3.1,制造执行系统MES,10
|
||||||
|
1.3.3.6,运维保障系统MRO,10
|
||||||
|
1.3.4,企业运营管理,8
|
||||||
|
1.3.3.4,可编程逻揖控制系统PLC,7
|
||||||
|
1.3.3.5,企业资产管理系统EAM,6
|
||||||
|
1.3.4.1,企业资源计划ERP,6
|
||||||
|
2.1.4.2.1,数据质量管理,5
|
||||||
|
2.1.4.2.2,数据安全管理,5
|
||||||
|
1.3.1.5,产品数据管理PDM,5
|
||||||
|
2.1.4,工业大数据,4
|
||||||
|
2.1.4.1.4,时序数据库,4
|
||||||
|
2.1.4.1.1,关系型数据库,3
|
||||||
|
2.1.4.1.2,分布式数据库,3
|
||||||
|
2.1.4.1.3,实时数据库,3
|
||||||
|
2.2,IaaS,3
|
||||||
|
1.3.1.3,计算机辅助制造CAM,2
|
||||||
|
1.3.3.7,故障预测与健康管理PHM,1
|
||||||
|
1.4.4.1,身份鉴别与访问控制,1
|
||||||
|
1.3.4.3,人力资源管理HRM,1
|
|
Before Width: | Height: | Size: 1.1 MiB After Width: | Height: | Size: 1.1 MiB |
After Width: | Height: | Size: 53 KiB |
After Width: | Height: | Size: 928 KiB |
Before Width: | Height: | Size: 3.0 MiB After Width: | Height: | Size: 3.0 MiB |
After Width: | Height: | Size: 2.7 MiB |
|
@ -0,0 +1,28 @@
|
||||||
|
,n_max_trial,crit_supplier,firm_pref_request,firm_pref_accept,netw_pref_cust_n,netw_pref_cust_size,cap_limit,diff_new_conn,diff_remove,X10,X11,X12,X13,n_disrupt_s,n_disrupt_t
|
||||||
|
0,15,2.0,2.0,2.0,0.5,2.0,4,0.5,0.5,0,0,0,0,888.0,2114.0
|
||||||
|
1,15,2.0,2.0,2.0,1.0,1.0,2,1.0,1.0,1,1,1,1,1297.0,2810.0
|
||||||
|
2,15,2.0,2.0,2.0,2.0,0.5,1,2.0,2.0,2,2,2,2,1826.0,3809.0
|
||||||
|
3,15,1.0,1.0,1.0,0.5,2.0,4,1.0,1.0,1,2,2,2,1372.0,3055.0
|
||||||
|
4,15,1.0,1.0,1.0,1.0,1.0,2,2.0,2.0,2,0,0,0,2118.0,4519.0
|
||||||
|
5,15,1.0,1.0,1.0,2.0,0.5,1,0.5,0.5,0,1,1,1,815.0,2073.0
|
||||||
|
6,15,0.5,0.5,0.5,0.5,2.0,4,2.0,2.0,2,1,1,1,2378.0,5528.0
|
||||||
|
7,15,0.5,0.5,0.5,1.0,1.0,2,0.5,0.5,0,2,2,2,968.0,2300.0
|
||||||
|
8,15,0.5,0.5,0.5,2.0,0.5,1,1.0,1.0,1,0,0,0,1531.0,3317.0
|
||||||
|
9,10,2.0,1.0,0.5,0.5,1.0,1,0.5,1.0,2,0,1,2,881.0,1972.0
|
||||||
|
10,10,2.0,1.0,0.5,1.0,0.5,4,1.0,2.0,0,1,2,0,1298.0,2763.0
|
||||||
|
11,10,2.0,1.0,0.5,2.0,2.0,2,2.0,0.5,1,2,0,1,1717.0,3837.0
|
||||||
|
12,10,1.0,0.5,2.0,0.5,1.0,1,1.0,2.0,0,2,0,1,1327.0,2855.0
|
||||||
|
13,10,1.0,0.5,2.0,1.0,0.5,4,2.0,0.5,1,0,1,2,2126.0,4788.0
|
||||||
|
14,10,1.0,0.5,2.0,2.0,2.0,2,0.5,1.0,2,1,2,0,801.0,1814.0
|
||||||
|
15,10,0.5,2.0,1.0,0.5,1.0,1,2.0,0.5,1,1,2,0,2442.0,5980.0
|
||||||
|
16,10,0.5,2.0,1.0,1.0,0.5,4,0.5,1.0,2,2,0,1,991.0,2186.0
|
||||||
|
17,10,0.5,2.0,1.0,2.0,2.0,2,1.0,2.0,0,0,1,2,1311.0,2776.0
|
||||||
|
18,5,2.0,0.5,1.0,0.5,0.5,2,0.5,2.0,1,0,2,1,879.0,1909.0
|
||||||
|
19,5,2.0,0.5,1.0,1.0,2.0,1,1.0,0.5,2,1,0,2,1354.0,3132.0
|
||||||
|
20,5,2.0,0.5,1.0,2.0,1.0,4,2.0,1.0,0,2,1,0,1727.0,3673.0
|
||||||
|
21,5,1.0,2.0,0.5,0.5,0.5,2,1.0,0.5,2,2,1,0,1379.0,3184.0
|
||||||
|
22,5,1.0,2.0,0.5,1.0,2.0,1,2.0,1.0,0,0,2,1,2145.0,4658.0
|
||||||
|
23,5,1.0,2.0,0.5,2.0,1.0,4,0.5,2.0,1,1,0,2,810.0,1764.0
|
||||||
|
24,5,0.5,1.0,2.0,0.5,0.5,2,2.0,1.0,0,1,0,2,2412.0,5783.0
|
||||||
|
25,5,0.5,1.0,2.0,1.0,2.0,1,0.5,2.0,1,2,1,0,915.0,1973.0
|
||||||
|
26,5,0.5,1.0,2.0,2.0,1.0,4,1.0,0.5,2,0,2,1,1336.0,3087.0
|
|
|
@ -1,28 +1,37 @@
|
||||||
,n_max_trial,crit_supplier,firm_pref_request,firm_pref_accept,netw_pref_cust_n,netw_pref_cust_size,cap_limit,diff_new_conn,diff_remove,X10,X11,X12,X13,n_disrupt_s,n_disrupt_t
|
idx_scenario,n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n,mean_count_firm_prod,mean_count_firm,mean_count_prod,mean_max_ts_firm_prod,mean_max_ts_firm,mean_max_ts_prod,mean_n_remove_firm_prod,mean_n_all_prod_remove_firm,mean_end_ts
|
||||||
0,15,2.0,2.0,2.0,0.5,2.0,4,0.5,0.5,0,0,0,0,888.0,2114.0
|
0,7,1,1,uniform,5.0000,0.3000,3,3,2.6375,2.6375,2.0861,1.0861,1.0861,1.0861,0.6034,0.2116,1.5507
|
||||||
1,15,2.0,2.0,2.0,1.0,1.0,2,1.0,1.0,1,1,1,1,1297.0,2810.0
|
1,5,1,1,uniform,10.0000,0.5000,5,2,2.7680,2.7657,2.2021,1.2021,1.2021,1.2021,0.8602,0.3032,2.2992
|
||||||
2,15,2.0,2.0,2.0,2.0,0.5,1,2.0,2.0,2,2,2,2,1826.0,3809.0
|
2,3,1,1,uniform,15.0000,0.7000,7,1,2.5724,2.5693,2.1728,1.1728,1.1728,1.1728,0.9326,0.3135,3.0844
|
||||||
3,15,1.0,1.0,1.0,0.5,2.0,4,1.0,1.0,1,2,2,2,1372.0,3055.0
|
3,7,1,1,uniform,5.0000,0.3000,3,2,2.6731,2.6731,2.1181,1.1181,1.1181,1.1181,0.6080,0.2147,1.5562
|
||||||
4,15,1.0,1.0,1.0,1.0,1.0,2,2.0,2.0,2,0,0,0,2118.0,4519.0
|
4,5,1,1,uniform,10.0000,0.5000,5,1,2.5528,2.5499,2.1568,1.1568,1.1568,1.1568,0.8128,0.2853,2.3352
|
||||||
5,15,1.0,1.0,1.0,2.0,0.5,1,0.5,0.5,0,1,1,1,815.0,2073.0
|
5,3,1,1,uniform,15.0000,0.7000,7,3,2.7758,2.7731,2.2036,1.2036,1.2036,1.2036,1.0053,0.3469,3.1764
|
||||||
6,15,0.5,0.5,0.5,0.5,2.0,4,2.0,2.0,2,1,1,1,2378.0,5528.0
|
6,7,1,1,normal,5.0000,0.5000,7,3,2.8051,2.8051,2.1349,1.1349,1.1349,1.1349,0.6017,0.2112,2.1840
|
||||||
7,15,0.5,0.5,0.5,1.0,1.0,2,0.5,0.5,0,2,2,2,968.0,2300.0
|
7,5,1,1,normal,10.0000,0.7000,3,2,2.4440,2.4432,2.0097,1.0097,1.0097,1.0097,0.6482,0.2261,1.5912
|
||||||
8,15,0.5,0.5,0.5,2.0,0.5,1,1.0,1.0,1,0,0,0,1531.0,3317.0
|
8,3,1,1,normal,15.0000,0.3000,5,1,2.5905,2.5857,2.1907,1.1907,1.1907,1.1907,0.8535,0.3027,2.5069
|
||||||
9,10,2.0,1.0,0.5,0.5,1.0,1,0.5,1.0,2,0,1,2,881.0,1972.0
|
9,7,1,0,uniform,5.0000,0.7000,5,3,2.6484,2.6484,2.0897,1.0897,1.0897,1.0897,0.6034,0.2116,1.8699
|
||||||
10,10,2.0,1.0,0.5,1.0,0.5,4,1.0,2.0,0,1,2,0,1298.0,2763.0
|
10,5,1,0,uniform,10.0000,0.3000,7,2,2.7800,2.7777,2.2126,1.2126,1.2126,1.2126,0.8669,0.3067,2.8625
|
||||||
11,10,2.0,1.0,0.5,2.0,2.0,2,2.0,0.5,1,2,0,1,1717.0,3837.0
|
11,3,1,0,uniform,15.0000,0.5000,3,1,2.6061,2.6008,2.2017,1.2017,1.2017,1.2017,1.0899,0.3779,2.0444
|
||||||
12,10,1.0,0.5,2.0,0.5,1.0,1,1.0,2.0,0,2,0,1,1327.0,2855.0
|
12,7,1,0,normal,10.0000,0.7000,3,1,2.4703,2.4701,2.0848,1.0848,1.0848,1.0848,0.6754,0.2326,1.6291
|
||||||
13,10,1.0,0.5,2.0,1.0,0.5,4,2.0,0.5,1,0,1,2,2126.0,4788.0
|
13,5,1,0,normal,15.0000,0.3000,5,3,2.8619,2.8602,2.1882,1.1882,1.1882,1.1882,0.8069,0.2745,2.2118
|
||||||
14,10,1.0,0.5,2.0,2.0,2.0,2,0.5,1.0,2,1,2,0,801.0,1814.0
|
14,3,1,0,normal,5.0000,0.5000,7,2,2.4358,2.4358,2.0008,1.0008,1.0008,1.0008,0.6013,0.2105,2.1909
|
||||||
15,10,0.5,2.0,1.0,0.5,1.0,1,2.0,0.5,1,1,2,0,2442.0,5980.0
|
15,7,1,0,normal,10.0000,0.7000,5,3,2.8232,2.8225,2.1522,1.1522,1.1522,1.1522,0.6636,0.2312,1.9735
|
||||||
16,10,0.5,2.0,1.0,1.0,0.5,4,0.5,1.0,2,2,0,1,991.0,2186.0
|
16,5,1,0,normal,15.0000,0.3000,7,2,2.4954,2.4939,2.0549,1.0549,1.0549,1.0549,0.7598,0.2646,2.6013
|
||||||
17,10,0.5,2.0,1.0,2.0,2.0,2,1.0,2.0,0,0,1,2,1311.0,2776.0
|
17,3,1,0,normal,5.0000,0.5000,3,1,2.4886,2.4880,2.1011,1.1011,1.1011,1.1011,0.7004,0.2467,1.6741
|
||||||
18,5,2.0,0.5,1.0,0.5,0.5,2,0.5,2.0,1,0,2,1,879.0,1909.0
|
18,7,0,1,normal,10.0000,0.3000,7,1,2.5133,2.5112,2.1253,1.1253,1.1253,1.1253,0.6949,0.2459,2.6966
|
||||||
19,5,2.0,0.5,1.0,1.0,2.0,1,1.0,0.5,2,1,0,2,1354.0,3132.0
|
19,5,0,1,normal,15.0000,0.5000,3,3,2.8387,2.8366,2.1686,1.1686,1.1686,1.1686,0.8318,0.2914,1.7528
|
||||||
20,5,2.0,0.5,1.0,2.0,1.0,4,2.0,1.0,0,2,1,0,1727.0,3673.0
|
20,3,0,1,normal,5.0000,0.7000,5,2,2.4606,2.4606,1.9937,0.9937,0.9937,0.9937,0.6004,0.2105,1.8640
|
||||||
21,5,1.0,2.0,0.5,0.5,0.5,2,1.0,0.5,2,2,1,0,1379.0,3184.0
|
21,7,0,1,normal,10.0000,0.5000,7,1,2.4653,2.4642,2.0829,1.0829,1.0829,1.0829,0.6514,0.2267,2.4522
|
||||||
22,5,1.0,2.0,0.5,1.0,2.0,1,2.0,1.0,0,0,2,1,2145.0,4658.0
|
22,5,0,1,normal,15.0000,0.7000,3,3,2.8364,2.8343,2.1667,1.1667,1.1667,1.1667,0.8267,0.2888,1.7461
|
||||||
23,5,1.0,2.0,0.5,2.0,1.0,4,0.5,2.0,1,1,0,2,810.0,1764.0
|
23,3,0,1,normal,5.0000,0.3000,5,2,2.4608,2.4608,1.9939,0.9939,0.9939,0.9939,0.6006,0.2107,1.8651
|
||||||
24,5,0.5,1.0,2.0,0.5,0.5,2,2.0,1.0,0,1,0,2,2412.0,5783.0
|
24,7,0,1,uniform,15.0000,0.5000,3,2,2.5840,2.5794,2.1474,1.1474,1.1474,1.1474,0.9568,0.3301,1.8722
|
||||||
25,5,0.5,1.0,2.0,1.0,2.0,1,0.5,2.0,1,2,1,0,915.0,1973.0
|
25,5,0,1,uniform,5.0000,0.7000,5,1,2.4339,2.4339,2.0541,1.0541,1.0541,1.0541,0.6048,0.2118,1.9189
|
||||||
26,5,0.5,1.0,2.0,2.0,1.0,4,1.0,0.5,2,0,2,1,1336.0,3087.0
|
26,3,0,1,uniform,10.0000,0.3000,7,3,2.7619,2.7602,2.1701,1.1701,1.1701,1.1701,0.8429,0.2994,2.8086
|
||||||
|
27,7,0,0,normal,15.0000,0.5000,5,2,2.5179,2.5160,2.0465,1.0465,1.0465,1.0465,0.7621,0.2688,2.1512
|
||||||
|
28,5,0,0,normal,5.0000,0.7000,7,1,2.4286,2.4284,2.0486,1.0486,1.0486,1.0486,0.6006,0.2105,2.2440
|
||||||
|
29,3,0,0,normal,10.0000,0.3000,3,3,2.7964,2.7962,2.1312,1.1312,1.1312,1.1312,0.6960,0.2406,1.6377
|
||||||
|
30,7,0,0,uniform,15.0000,0.7000,7,2,2.5851,2.5806,2.1476,1.1476,1.1476,1.1476,0.9295,0.3154,2.9756
|
||||||
|
31,5,0,0,uniform,5.0000,0.3000,3,1,2.4966,2.4952,2.1103,1.1103,1.1103,1.1103,0.8017,0.2952,1.7958
|
||||||
|
32,3,0,0,uniform,10.0000,0.5000,5,3,2.7703,2.7686,2.1771,1.1771,1.1771,1.1771,0.8387,0.2956,2.3099
|
||||||
|
33,7,0,0,uniform,15.0000,0.3000,5,1,2.6002,2.5941,2.2002,1.2002,1.2002,1.2002,1.0322,0.3707,2.7615
|
||||||
|
34,5,0,0,uniform,5.0000,0.5000,7,3,2.6827,2.6827,2.0994,1.0994,1.0994,1.0994,0.6025,0.2122,2.1867
|
||||||
|
35,3,0,0,uniform,10.0000,0.7000,3,2,2.5514,2.5495,2.1181,1.1181,1.1181,1.1181,0.8352,0.2867,1.7676
|
||||||
|
|
|
Before Width: | Height: | Size: 928 KiB After Width: | Height: | Size: 1.0 MiB |
Before Width: | Height: | Size: 2.7 MiB After Width: | Height: | Size: 2.5 MiB |
|
@ -5,4 +5,4 @@ print(count)
|
||||||
print(len(count['s_id'].unique()))
|
print(len(count['s_id'].unique()))
|
||||||
count_max_ts = count.groupby('s_id')['ts'].max()
|
count_max_ts = count.groupby('s_id')['ts'].max()
|
||||||
print(count_max_ts.value_counts())
|
print(count_max_ts.value_counts())
|
||||||
print(count_max_ts.value_counts()/1593)
|
print(count_max_ts.value_counts()/1593)
|
||||||
|
|
|
@ -6,7 +6,6 @@ plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||||
|
|
||||||
# count firm category
|
# count firm category
|
||||||
count_firm = pd.read_csv("analysis\\count_firm.csv")
|
count_firm = pd.read_csv("analysis\\count_firm.csv")
|
||||||
count_firm = count_firm[count_firm['count'] > 4]
|
|
||||||
print(count_firm.describe())
|
print(count_firm.describe())
|
||||||
|
|
||||||
count_dcp = pd.read_csv("analysis\\count_dcp.csv",
|
count_dcp = pd.read_csv("analysis\\count_dcp.csv",
|
||||||
|
@ -15,7 +14,7 @@ count_dcp = pd.read_csv("analysis\\count_dcp.csv",
|
||||||
'down_id_firm': str
|
'down_id_firm': str
|
||||||
})
|
})
|
||||||
# print(count_dcp)
|
# print(count_dcp)
|
||||||
count_dcp = count_dcp[count_dcp['count'] > 2]
|
count_dcp = count_dcp[count_dcp['count'] > 35]
|
||||||
|
|
||||||
list_firm = count_dcp['up_id_firm'].tolist(
|
list_firm = count_dcp['up_id_firm'].tolist(
|
||||||
) + count_dcp['down_id_firm'].tolist()
|
) + count_dcp['down_id_firm'].tolist()
|
||||||
|
@ -53,7 +52,6 @@ for _, row in count_dcp.iterrows():
|
||||||
'up_name_product': row['up_name_product'],
|
'up_name_product': row['up_name_product'],
|
||||||
'down_id_product': row['down_id_product'],
|
'down_id_product': row['down_id_product'],
|
||||||
'down_name_product': row['down_name_product'],
|
'down_name_product': row['down_name_product'],
|
||||||
# 'edge_label': f"{row['up_id_product']} {row['up_name_product']} - {row['down_id_product']} {row['down_name_product']}",
|
|
||||||
'edge_label': f"{row['up_id_product']} - {row['down_id_product']}",
|
'edge_label': f"{row['up_id_product']} - {row['down_id_product']}",
|
||||||
'edge_width': k * (row['count'] - count_min),
|
'edge_width': k * (row['count'] - count_min),
|
||||||
'count': row['count']
|
'count': row['count']
|
||||||
|
@ -87,7 +85,7 @@ nx.draw(G_firm,
|
||||||
pos,
|
pos,
|
||||||
node_size=node_size,
|
node_size=node_size,
|
||||||
labels=node_label,
|
labels=node_label,
|
||||||
font_size=6,
|
font_size=8,
|
||||||
width=3,
|
width=3,
|
||||||
edge_color=colors,
|
edge_color=colors,
|
||||||
edge_cmap=cmap,
|
edge_cmap=cmap,
|
||||||
|
@ -96,7 +94,9 @@ nx.draw(G_firm,
|
||||||
nx.draw_networkx_edge_labels(G_firm, pos, edge_label, font_size=6)
|
nx.draw_networkx_edge_labels(G_firm, pos, edge_label, font_size=6)
|
||||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||||
sm._A = []
|
sm._A = []
|
||||||
position = fig.add_axes([0.9, 0.05, 0.01, 0.3])
|
position = fig.add_axes([0.95, 0.05, 0.01, 0.3])
|
||||||
plt.colorbar(sm, fraction=0.01, cax=position)
|
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||||
plt.savefig("analysis\\count_dcp_network20230526_de")
|
cb.ax.tick_params(labelsize=10)
|
||||||
|
cb.outline.set_visible(False)
|
||||||
|
plt.savefig("analysis\\count_dcp_network")
|
||||||
plt.close()
|
plt.close()
|
||||||
|
|
|
@ -1,8 +1,6 @@
|
||||||
import pandas as pd
|
import pandas as pd
|
||||||
import numpy as np
|
|
||||||
import matplotlib.pyplot as plt
|
import matplotlib.pyplot as plt
|
||||||
import networkx as nx
|
import networkx as nx
|
||||||
import math
|
|
||||||
|
|
||||||
plt.rcParams['font.sans-serif'] = 'SimHei'
|
plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||||
|
|
||||||
|
@ -32,7 +30,7 @@ for code in G.nodes:
|
||||||
index_list = count_prod[count_prod['id_product'] == code].index.tolist()
|
index_list = count_prod[count_prod['id_product'] == code].index.tolist()
|
||||||
index = index_list[0] if len(index_list) == 1 else -1
|
index = index_list[0] if len(index_list) == 1 else -1
|
||||||
node_attr['count'] = count_prod['count'].get(index, 0)
|
node_attr['count'] = count_prod['count'].get(index, 0)
|
||||||
node_attr['node_size'] = 5 * count_prod['count'].get(index, 0)
|
node_attr['node_size'] = count_prod['count'].get(index, 0)
|
||||||
node_attr['node_color'] = count_prod['count'].get(index, 0)
|
node_attr['node_color'] = count_prod['count'].get(index, 0)
|
||||||
labels_dict[code] = node_attr
|
labels_dict[code] = node_attr
|
||||||
nx.set_node_attributes(G, labels_dict)
|
nx.set_node_attributes(G, labels_dict)
|
||||||
|
@ -62,8 +60,10 @@ nx.draw(G,
|
||||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||||
sm._A = []
|
sm._A = []
|
||||||
position = fig.add_axes([0.01, 0.05, 0.01, 0.3])
|
position = fig.add_axes([0.01, 0.05, 0.01, 0.3])
|
||||||
plt.colorbar(sm, fraction=0.01, cax=position)
|
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||||
# plt.savefig("analysis\\count_prod_network")
|
cb.ax.tick_params(labelsize=8)
|
||||||
|
cb.outline.set_visible(False)
|
||||||
|
plt.savefig("analysis\\count_prod_network")
|
||||||
plt.close()
|
plt.close()
|
||||||
|
|
||||||
# dcp_prod
|
# dcp_prod
|
||||||
|
@ -72,13 +72,17 @@ count_dcp = pd.read_csv("analysis\\count_dcp.csv",
|
||||||
'up_id_firm': str,
|
'up_id_firm': str,
|
||||||
'down_id_firm': str
|
'down_id_firm': str
|
||||||
})
|
})
|
||||||
count_dcp_prod = count_dcp.groupby(['up_id_product','up_name_product', 'down_id_product', 'down_name_product'])['count'].sum()
|
count_dcp_prod = count_dcp.groupby(
|
||||||
|
['up_id_product',
|
||||||
|
'up_name_product',
|
||||||
|
'down_id_product',
|
||||||
|
'down_name_product'])['count'].sum()
|
||||||
count_dcp_prod = count_dcp_prod.reset_index()
|
count_dcp_prod = count_dcp_prod.reset_index()
|
||||||
count_dcp_prod.sort_values('count', inplace=True, ascending=False)
|
count_dcp_prod.sort_values('count', inplace=True, ascending=False)
|
||||||
count_dcp_prod.to_csv('analysis\\count_dcp_prod.csv',
|
count_dcp_prod.to_csv('analysis\\count_dcp_prod.csv',
|
||||||
index=False,
|
index=False,
|
||||||
encoding='utf-8-sig')
|
encoding='utf-8-sig')
|
||||||
count_dcp_prod = count_dcp_prod[count_dcp_prod['count'] > 2]
|
count_dcp_prod = count_dcp_prod[count_dcp_prod['count'] > 50]
|
||||||
# print(count_dcp_prod)
|
# print(count_dcp_prod)
|
||||||
|
|
||||||
list_prod = count_dcp_prod['up_id_product'].tolist(
|
list_prod = count_dcp_prod['up_id_product'].tolist(
|
||||||
|
@ -116,6 +120,8 @@ for _, row in count_dcp_prod.iterrows():
|
||||||
# dcp_networkx
|
# dcp_networkx
|
||||||
pos = nx.nx_agraph.graphviz_layout(g_bom, prog="dot", args="")
|
pos = nx.nx_agraph.graphviz_layout(g_bom, prog="dot", args="")
|
||||||
node_labels = nx.get_node_attributes(g_bom, 'Name')
|
node_labels = nx.get_node_attributes(g_bom, 'Name')
|
||||||
|
# rename node 1
|
||||||
|
node_labels['1'] = '解决方案'
|
||||||
temp = {}
|
temp = {}
|
||||||
for key, value in node_labels.items():
|
for key, value in node_labels.items():
|
||||||
temp[key] = key + " " + value
|
temp[key] = key + " " + value
|
||||||
|
@ -126,28 +132,7 @@ vmin = min(colors)
|
||||||
vmax = max(colors)
|
vmax = max(colors)
|
||||||
cmap = plt.cm.Blues
|
cmap = plt.cm.Blues
|
||||||
|
|
||||||
# dct_row = {}
|
pos_new = {}
|
||||||
# for node, p in pos.items():
|
|
||||||
# if p[1] not in dct_row.keys():
|
|
||||||
# dct_row[p[1]] = {node: p}
|
|
||||||
# else:
|
|
||||||
# dct_row[p[1]][node] = p
|
|
||||||
# dct_row = dict(sorted(dct_row.items(), key=lambda d: d[0], reverse=True))
|
|
||||||
# dct_up = dct_row[max(dct_row.keys())]
|
|
||||||
# dct_up = dict(sorted(dct_up.items(), key=lambda d: d[1][0], reverse=True))
|
|
||||||
# h = list(dct_row.keys())[0] - list(dct_row.keys())[1]
|
|
||||||
# n = len(dct_up.items())
|
|
||||||
# arr_h = np.linspace(list(dct_row.keys())[0]-h/2, list(dct_row.keys())[0]+2*h, num=n)
|
|
||||||
# dct_up_new = {}
|
|
||||||
# for index, (node, p) in enumerate(dct_up.items()):
|
|
||||||
# dct_up_new[node] = (p[0], arr_h[index])
|
|
||||||
# pos_new = {}
|
|
||||||
# for row, dct in dct_row.items():
|
|
||||||
# if row == list(dct_row.keys())[0]:
|
|
||||||
# pos_new.update(dct_up_new)
|
|
||||||
# else:
|
|
||||||
# pos_new.update(dct)
|
|
||||||
pos_new ={}
|
|
||||||
for node, p in pos.items():
|
for node, p in pos.items():
|
||||||
pos_new[node] = (p[1], p[0])
|
pos_new[node] = (p[1], p[0])
|
||||||
|
|
||||||
|
@ -157,8 +142,8 @@ nx.draw(g_bom,
|
||||||
pos_new,
|
pos_new,
|
||||||
node_size=50,
|
node_size=50,
|
||||||
labels=node_labels,
|
labels=node_labels,
|
||||||
font_size=6,
|
font_size=5,
|
||||||
width = 1.5,
|
width=1.5,
|
||||||
edge_color=colors,
|
edge_color=colors,
|
||||||
edge_cmap=cmap,
|
edge_cmap=cmap,
|
||||||
edge_vmin=vmin,
|
edge_vmin=vmin,
|
||||||
|
@ -170,7 +155,9 @@ axis.set_ylim([1.2*y for y in axis.get_ylim()])
|
||||||
|
|
||||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||||
sm._A = []
|
sm._A = []
|
||||||
position=fig.add_axes([0.1, 0.4, 0.01, 0.2])
|
position = fig.add_axes([0.75, 0.1, 0.01, 0.2])
|
||||||
plt.colorbar(sm, fraction=0.01, cax=position)
|
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||||
# plt.savefig("analysis\\count_dcp_prod_network")
|
cb.ax.tick_params(labelsize=8)
|
||||||
plt.close()
|
cb.outline.set_visible(False)
|
||||||
|
plt.savefig("analysis\\count_dcp_prod_network")
|
||||||
|
plt.close()
|
||||||
|
|
|
@ -10,20 +10,13 @@ Firm['Code'] = Firm['Code'].astype('string')
|
||||||
Firm.fillna(0, inplace=True)
|
Firm.fillna(0, inplace=True)
|
||||||
BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
|
BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
|
||||||
|
|
||||||
result = pd.read_sql(sql='select * from iiabmdb_dissertation.not_test_result where ts > 0;',
|
with open('SQL_analysis_risk.sql', 'r') as f:
|
||||||
|
str_sql = f.read()
|
||||||
|
result = pd.read_sql(sql=str_sql,
|
||||||
con=engine)
|
con=engine)
|
||||||
lst_s_id = list(set(result['s_id'].to_list()))
|
result.to_csv('analysis\\count.csv',
|
||||||
for s_id in lst_s_id:
|
index=False,
|
||||||
query = pd.read_sql(
|
encoding='utf-8-sig')
|
||||||
sql=f'select * from iiabmdb_dissertation.not_test_result where ts = 0 and s_id = {s_id};',
|
|
||||||
con=engine)
|
|
||||||
result = pd.concat([result, query])
|
|
||||||
result.set_index('id', inplace=True)
|
|
||||||
result.sort_index(inplace=True)
|
|
||||||
result['id_firm'] = result['id_firm'].astype('string')
|
|
||||||
# result.to_csv('analysis\\count.csv',
|
|
||||||
# index=False,
|
|
||||||
# encoding='utf-8-sig')
|
|
||||||
print(result)
|
print(result)
|
||||||
|
|
||||||
# G bom
|
# G bom
|
||||||
|
@ -31,17 +24,20 @@ plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||||
|
|
||||||
exp_id = 1
|
exp_id = 1
|
||||||
G_bom_str = pd.read_sql(
|
G_bom_str = pd.read_sql(
|
||||||
sql=f'select g_bom from iiabmdb_dissertation.not_test_experiment where id = {exp_id};',
|
sql=f'select g_bom from iiabmdb.without_exp_experiment '
|
||||||
|
f'where id = {exp_id};',
|
||||||
con=engine)['g_bom'].tolist()[0]
|
con=engine)['g_bom'].tolist()[0]
|
||||||
G_bom = nx.adjacency_graph(json.loads(G_bom_str))
|
G_bom = nx.adjacency_graph(json.loads(G_bom_str))
|
||||||
pos = nx.nx_agraph.graphviz_layout(G_bom, prog="twopi", args="")
|
pos = nx.nx_agraph.graphviz_layout(G_bom, prog="twopi", args="")
|
||||||
node_labels = nx.get_node_attributes(G_bom, 'Name')
|
node_labels = nx.get_node_attributes(G_bom, 'Name')
|
||||||
|
# rename node 1
|
||||||
|
node_labels['1'] = '解决方案'
|
||||||
plt.figure(figsize=(12, 12), dpi=300)
|
plt.figure(figsize=(12, 12), dpi=300)
|
||||||
nx.draw_networkx_nodes(G_bom, pos)
|
nx.draw_networkx_nodes(G_bom, pos)
|
||||||
nx.draw_networkx_edges(G_bom, pos)
|
nx.draw_networkx_edges(G_bom, pos)
|
||||||
nx.draw_networkx_labels(G_bom, pos, labels=node_labels, font_size=6)
|
nx.draw_networkx_labels(G_bom, pos, labels=node_labels, font_size=6)
|
||||||
# plt.show()
|
# plt.show()
|
||||||
# plt.savefig(f"analysis\\g_bom_exp_id_{exp_id}.png")
|
plt.savefig(f"analysis\\g_bom_exp_id_{exp_id}.png")
|
||||||
plt.close()
|
plt.close()
|
||||||
|
|
||||||
# G firm
|
# G firm
|
||||||
|
@ -49,7 +45,7 @@ plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||||
|
|
||||||
sample_id = 1
|
sample_id = 1
|
||||||
G_firm_str = pd.read_sql(
|
G_firm_str = pd.read_sql(
|
||||||
sql=f'select g_firm from iiabmdb_dissertation.not_test_sample where id = {exp_id};',
|
sql=f'select g_firm from iiabmdb.without_exp_sample where id = {exp_id};',
|
||||||
con=engine)['g_firm'].tolist()[0]
|
con=engine)['g_firm'].tolist()[0]
|
||||||
G_firm = nx.adjacency_graph(json.loads(G_firm_str))
|
G_firm = nx.adjacency_graph(json.loads(G_firm_str))
|
||||||
pos = nx.nx_agraph.graphviz_layout(G_firm, prog="twopi", args="")
|
pos = nx.nx_agraph.graphviz_layout(G_firm, prog="twopi", args="")
|
||||||
|
@ -91,9 +87,9 @@ count_firm_prod.rename(columns={'Name': 'name_product'}, inplace=True)
|
||||||
count_firm_prod = count_firm_prod[[
|
count_firm_prod = count_firm_prod[[
|
||||||
'id_firm', 'name_firm', 'id_product', 'name_product', 'count'
|
'id_firm', 'name_firm', 'id_product', 'name_product', 'count'
|
||||||
]]
|
]]
|
||||||
# count_firm_prod.to_csv('analysis\\count_firm_prod.csv',
|
count_firm_prod.to_csv('analysis\\count_firm_prod.csv',
|
||||||
# index=False,
|
index=False,
|
||||||
# encoding='utf-8-sig')
|
encoding='utf-8-sig')
|
||||||
print(count_firm_prod)
|
print(count_firm_prod)
|
||||||
|
|
||||||
# count firm
|
# count firm
|
||||||
|
@ -107,9 +103,9 @@ count_firm = pd.merge(count_firm,
|
||||||
count_firm.drop('Code', axis=1, inplace=True)
|
count_firm.drop('Code', axis=1, inplace=True)
|
||||||
count_firm.sort_values('count', inplace=True, ascending=False)
|
count_firm.sort_values('count', inplace=True, ascending=False)
|
||||||
count_firm = count_firm[['id_firm', 'Name', 'count']]
|
count_firm = count_firm[['id_firm', 'Name', 'count']]
|
||||||
# count_firm.to_csv('analysis\\count_firm.csv',
|
count_firm.to_csv('analysis\\count_firm.csv',
|
||||||
# index=False,
|
index=False,
|
||||||
# encoding='utf-8-sig')
|
encoding='utf-8-sig')
|
||||||
print(count_firm)
|
print(count_firm)
|
||||||
|
|
||||||
# count product
|
# count product
|
||||||
|
@ -123,14 +119,13 @@ count_prod = pd.merge(count_prod,
|
||||||
count_prod.drop('Code', axis=1, inplace=True)
|
count_prod.drop('Code', axis=1, inplace=True)
|
||||||
count_prod.sort_values('count', inplace=True, ascending=False)
|
count_prod.sort_values('count', inplace=True, ascending=False)
|
||||||
count_prod = count_prod[['id_product', 'Name', 'count']]
|
count_prod = count_prod[['id_product', 'Name', 'count']]
|
||||||
# count_prod.to_csv('analysis\\count_prod.csv',
|
count_prod.to_csv('analysis\\count_prod.csv',
|
||||||
# index=False,
|
index=False,
|
||||||
# encoding='utf-8-sig')
|
encoding='utf-8-sig')
|
||||||
print(count_prod)
|
print(count_prod)
|
||||||
|
|
||||||
# DCP disruption causing probability
|
# DCP disruption causing probability
|
||||||
result_disrupt_ts_above_0 = result[(result['ts'] > 0)
|
result_disrupt_ts_above_0 = result[result['ts'] > 0]
|
||||||
& (result['is_disrupted'] == 1)]
|
|
||||||
print(result_disrupt_ts_above_0)
|
print(result_disrupt_ts_above_0)
|
||||||
result_dcp = pd.DataFrame(columns=[
|
result_dcp = pd.DataFrame(columns=[
|
||||||
's_id', 'up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product'
|
's_id', 'up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product'
|
||||||
|
@ -188,5 +183,5 @@ count_dcp = count_dcp[[
|
||||||
'down_id_firm', 'down_name_firm', 'down_id_product', 'down_name_product',
|
'down_id_firm', 'down_name_firm', 'down_id_product', 'down_name_product',
|
||||||
'count'
|
'count'
|
||||||
]]
|
]]
|
||||||
# count_dcp.to_csv('analysis\\count_dcp.csv', index=False, encoding='utf-8-sig')
|
count_dcp.to_csv('analysis\\count_dcp.csv', index=False, encoding='utf-8-sig')
|
||||||
print(count_dcp)
|
print(count_dcp)
|
41
anova.py
|
@ -110,49 +110,16 @@ def anova(lst_col_seg, n_level, oa_file, result_file, alpha=0.1):
|
||||||
|
|
||||||
if __name__ == '__main__':
|
if __name__ == '__main__':
|
||||||
# prep data
|
# prep data
|
||||||
str_sql = """
|
result = pd.read_csv("experiment_result.csv", index_col=None)
|
||||||
select * from
|
|
||||||
(select distinct idx_scenario, n_max_trial, crit_supplier,
|
|
||||||
firm_pref_request, firm_pref_accept, netw_pref_cust_n,
|
|
||||||
netw_pref_cust_size, cap_limit, diff_new_conn, diff_remove
|
|
||||||
from iiabmdb.with_exp_experiment) as a
|
|
||||||
inner join
|
|
||||||
(
|
|
||||||
select idx_scenario,
|
|
||||||
sum(n_disrupt_s) as n_disrupt_s, sum(n_disrupt_t) as n_disrupt_t from
|
|
||||||
iiabmdb.with_exp_experiment as a
|
|
||||||
inner join
|
|
||||||
(
|
|
||||||
select e_id, count(n_s_disrupt_t) as n_disrupt_s,
|
|
||||||
sum(n_s_disrupt_t) as n_disrupt_t from
|
|
||||||
iiabmdb.with_exp_sample as a
|
|
||||||
inner join
|
|
||||||
(select a.s_id as s_id, count(id) as n_s_disrupt_t from
|
|
||||||
iiabmdb.with_exp_result as a
|
|
||||||
inner join
|
|
||||||
(select distinct s_id from iiabmdb.with_exp_result where ts > 0) as b
|
|
||||||
on a.s_id = b.s_id
|
|
||||||
group by s_id
|
|
||||||
) as b
|
|
||||||
on a.id = b.s_id
|
|
||||||
group by e_id
|
|
||||||
) as b
|
|
||||||
on a.id = b.e_id
|
|
||||||
group by idx_scenario) as b
|
|
||||||
on a.idx_scenario = b.idx_scenario;
|
|
||||||
|
|
||||||
"""
|
|
||||||
result = pd.read_sql(sql=str_sql,
|
|
||||||
con=engine)
|
|
||||||
result.drop('idx_scenario', 1, inplace=True)
|
result.drop('idx_scenario', 1, inplace=True)
|
||||||
df_oa = pd.read_csv("oa_with_exp.csv", index_col=None)
|
df_oa = pd.read_csv("oa_with_exp.csv", index_col=None)
|
||||||
result = pd.concat(
|
scenario_result = pd.concat(
|
||||||
[result.iloc[:, 0:10],
|
[result.iloc[:, 0:10],
|
||||||
df_oa.iloc[:, -4:],
|
df_oa.iloc[:, -4:],
|
||||||
result.iloc[:, -2:]], axis=1)
|
result.iloc[:, -2:]], axis=1)
|
||||||
result.to_csv('analysis\\experiment_result.csv')
|
result.to_csv('analysis\\experiment_result.csv')
|
||||||
|
|
||||||
# 9 factors (X), 4 for error (E), and 2 indicators (Y)
|
# 10 factors (X), 13 for error (E), and 9 indicators (Y)
|
||||||
the_lst_col_seg = [10, 3, 2]
|
the_lst_col_seg = [10, 13, 9]
|
||||||
the_n_level = 3
|
the_n_level = 3
|
||||||
anova(the_lst_col_seg, the_n_level, "oa25.txt", result, 0.1)
|
anova(the_lst_col_seg, the_n_level, "oa25.txt", result, 0.1)
|
||||||
|
|
BIN
anova.xlsx
|
@ -0,0 +1,14 @@
|
||||||
|
import pandas as pd
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
import seaborn as sns
|
||||||
|
|
||||||
|
df_anova = pd.read_csv('analysis/anova.csv', index_col=0)
|
||||||
|
df_anova = df_anova.stack().reset_index()
|
||||||
|
df_anova.rename(columns={'level_0': 'x',
|
||||||
|
'level_1': 'y type',
|
||||||
|
0: 'p value'}, inplace=True)
|
||||||
|
print(df_anova)
|
||||||
|
sns.set_theme(style="whitegrid")
|
||||||
|
g = sns.catplot(data=df_anova, kind="bar", x="x", y="p value", hue="y type")
|
||||||
|
g.set_xticklabels(rotation=30)
|
||||||
|
plt.show()
|
|
@ -1 +1 @@
|
||||||
db_name_prefix: test
|
db_name_prefix: with_exp
|
||||||
|
|
|
@ -1,7 +1,7 @@
|
||||||
# read by ControllerDB
|
# read by ControllerDB
|
||||||
|
|
||||||
# run settings
|
# run settings
|
||||||
meta_seed: 0
|
meta_seed: 1
|
||||||
|
|
||||||
test: # only for test scenarios
|
test: # only for test scenarios
|
||||||
n_sample: 1
|
n_sample: 1
|
||||||
|
|
|
@ -54,24 +54,13 @@ class ControllerDB:
|
||||||
# fill dct_lst_init_disrupt_firm_prod
|
# fill dct_lst_init_disrupt_firm_prod
|
||||||
list_dct = []
|
list_dct = []
|
||||||
if self.is_with_exp:
|
if self.is_with_exp:
|
||||||
str_sql = "select e_id, count, max_max_ts, " \
|
with open('SQL_export_high_risk_setting.sql', 'r') as f:
|
||||||
"dct_lst_init_disrupt_firm_prod from " \
|
str_sql = f.read()
|
||||||
"iiabmdb.without_exp_experiment as a " \
|
|
||||||
"inner join " \
|
|
||||||
"(select e_id, count(id) as count, max(max_ts) as max_max_ts "\
|
|
||||||
"from iiabmdb.without_exp_sample as a " \
|
|
||||||
"inner join (select s_id, max(ts) as max_ts from " \
|
|
||||||
"iiabmdb.without_exp_result where ts > 0 group by s_id) as b "\
|
|
||||||
"on a.id = b.s_id " \
|
|
||||||
"group by e_id) as b " \
|
|
||||||
"on a.id = b.e_id " \
|
|
||||||
"order by count desc;"
|
|
||||||
result = pd.read_sql(sql=str_sql, con=engine)
|
result = pd.read_sql(sql=str_sql, con=engine)
|
||||||
result['dct_lst_init_disrupt_firm_prod'] = \
|
result['dct_lst_init_disrupt_firm_prod'] = \
|
||||||
result['dct_lst_init_disrupt_firm_prod'].apply(
|
result['dct_lst_init_disrupt_firm_prod'].apply(
|
||||||
lambda x: pickle.loads(x))
|
lambda x: pickle.loads(x))
|
||||||
list_dct = result.loc[result['count'] > 10,
|
list_dct = result['dct_lst_init_disrupt_firm_prod'].to_list()
|
||||||
'dct_lst_init_disrupt_firm_prod'].to_list()
|
|
||||||
else:
|
else:
|
||||||
for _, row in Firm.iterrows():
|
for _, row in Firm.iterrows():
|
||||||
code = row['Code']
|
code = row['Code']
|
||||||
|
@ -82,10 +71,11 @@ class ControllerDB:
|
||||||
# list_dct = [{'140': ['1.4.5.1']}]
|
# list_dct = [{'140': ['1.4.5.1']}]
|
||||||
# list_dct = [{'133': ['1.4.4.1']}]
|
# list_dct = [{'133': ['1.4.4.1']}]
|
||||||
# list_dct = [{'2': ['1.1.3']}]
|
# list_dct = [{'2': ['1.1.3']}]
|
||||||
list_dct = [{'135': ['1.3.2.1']}]
|
# list_dct = [{'135': ['1.3.2.1']}]
|
||||||
# list_dct = [{'79': ['2.1.3.4']}]
|
# list_dct = [{'79': ['2.1.3.4']}]
|
||||||
# list_dct = [{'99': ['1.3.3']}]
|
# list_dct = [{'99': ['1.3.3']}]
|
||||||
# list_dct = [{'41': ['1.4.5']}]
|
# list_dct = [{'41': ['1.4.5']}]
|
||||||
|
# list_dct = [{'168': ['1.1.2']}]
|
||||||
|
|
||||||
# fill g_bom
|
# fill g_bom
|
||||||
BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
|
BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
|
||||||
|
@ -128,8 +118,7 @@ class ControllerDB:
|
||||||
dct_lst_init_disrupt_firm_prod, g_bom,
|
dct_lst_init_disrupt_firm_prod, g_bom,
|
||||||
n_max_trial, prf_size, prf_conn,
|
n_max_trial, prf_size, prf_conn,
|
||||||
cap_limit_prob_type, cap_limit_level,
|
cap_limit_prob_type, cap_limit_level,
|
||||||
diff_new_conn, crit_supplier,
|
diff_new_conn, remove_t, netw_prf_n):
|
||||||
proactive_ratio, remove_t, netw_prf_n):
|
|
||||||
e = Experiment(
|
e = Experiment(
|
||||||
idx_scenario=idx_scenario,
|
idx_scenario=idx_scenario,
|
||||||
idx_init_removal=idx_init_removal,
|
idx_init_removal=idx_init_removal,
|
||||||
|
@ -143,8 +132,6 @@ class ControllerDB:
|
||||||
cap_limit_prob_type=cap_limit_prob_type,
|
cap_limit_prob_type=cap_limit_prob_type,
|
||||||
cap_limit_level=cap_limit_level,
|
cap_limit_level=cap_limit_level,
|
||||||
diff_new_conn=diff_new_conn,
|
diff_new_conn=diff_new_conn,
|
||||||
crit_supplier=crit_supplier,
|
|
||||||
proactive_ratio=proactive_ratio,
|
|
||||||
remove_t=remove_t,
|
remove_t=remove_t,
|
||||||
netw_prf_n=netw_prf_n
|
netw_prf_n=netw_prf_n
|
||||||
)
|
)
|
||||||
|
|
After Width: | Height: | Size: 501 KiB |
After Width: | Height: | Size: 718 KiB |
After Width: | Height: | Size: 160 KiB |
After Width: | Height: | Size: 184 KiB |
After Width: | Height: | Size: 188 KiB |
After Width: | Height: | Size: 195 KiB |
After Width: | Height: | Size: 129 KiB |
After Width: | Height: | Size: 162 KiB |
223
firm.py
|
@ -1,5 +1,4 @@
|
||||||
import agentpy as ap
|
import agentpy as ap
|
||||||
import math
|
|
||||||
|
|
||||||
|
|
||||||
class FirmAgent(ap.Agent):
|
class FirmAgent(ap.Agent):
|
||||||
|
@ -7,7 +6,7 @@ class FirmAgent(ap.Agent):
|
||||||
self.firm_network = self.model.firm_network
|
self.firm_network = self.model.firm_network
|
||||||
self.product_network = self.model.product_network
|
self.product_network = self.model.product_network
|
||||||
|
|
||||||
# self para
|
# self parameter
|
||||||
self.code = code
|
self.code = code
|
||||||
self.name = name
|
self.name = name
|
||||||
self.type_region = type_region
|
self.type_region = type_region
|
||||||
|
@ -15,7 +14,7 @@ class FirmAgent(ap.Agent):
|
||||||
self.dct_prod_up_prod_stat = {}
|
self.dct_prod_up_prod_stat = {}
|
||||||
self.dct_prod_capacity = {}
|
self.dct_prod_capacity = {}
|
||||||
|
|
||||||
# para in trial
|
# parameter in trial
|
||||||
self.dct_n_trial_up_prod_disrupted = {}
|
self.dct_n_trial_up_prod_disrupted = {}
|
||||||
self.dct_cand_alt_supp_up_prod_disrupted = {}
|
self.dct_cand_alt_supp_up_prod_disrupted = {}
|
||||||
self.dct_request_prod_from_firm = {}
|
self.dct_request_prod_from_firm = {}
|
||||||
|
@ -26,24 +25,27 @@ class FirmAgent(ap.Agent):
|
||||||
self.str_cap_limit_prob_type = str(self.p.cap_limit_prob_type)
|
self.str_cap_limit_prob_type = str(self.p.cap_limit_prob_type)
|
||||||
self.flt_cap_limit_level = float(self.p.cap_limit_level)
|
self.flt_cap_limit_level = float(self.p.cap_limit_level)
|
||||||
self.flt_diff_new_conn = float(self.p.diff_new_conn)
|
self.flt_diff_new_conn = float(self.p.diff_new_conn)
|
||||||
self.flt_crit_supplier = float(self.p.crit_supplier)
|
|
||||||
|
|
||||||
# init size_stat (self para)
|
# initialize size_stat (self parameter)
|
||||||
# (size, time step)
|
# (size, time step)
|
||||||
self.size_stat.append((revenue_log, 0))
|
self.size_stat.append((revenue_log, 0))
|
||||||
|
|
||||||
# init dct_prod_up_prod_stat (self para)
|
# init dct_prod_up_prod_stat (self parameter)
|
||||||
for prod in a_lst_product:
|
for prod in a_lst_product:
|
||||||
self.dct_prod_up_prod_stat[prod] = {
|
self.dct_prod_up_prod_stat[prod] = {
|
||||||
# (Normal / Disrupted / Removed, time step)
|
# status: (Normal / Disrupted / Removed, time step)
|
||||||
'status': [('N', 0)],
|
'p_stat': [('N', 0)],
|
||||||
# have or have no supply
|
# supply for each component and respective disrupted supplier
|
||||||
'supply': dict.fromkeys(prod.a_predecessors(), True)
|
# set_disrupt_firm is refreshed to empty at each update
|
||||||
|
's_stat': {up_prod: {'stat': True,
|
||||||
|
'set_disrupt_firm': set()}
|
||||||
|
for up_prod in prod.a_predecessors()}
|
||||||
|
# Note: do not use fromkeys as it's a shallow copy
|
||||||
}
|
}
|
||||||
|
|
||||||
# init extra capacity (self para)
|
# initialize extra capacity (self parameter)
|
||||||
for product in a_lst_product:
|
for product in a_lst_product:
|
||||||
# init extra capacity based on discrete uniform distribution
|
# initialize extra capacity based on discrete uniform distribution
|
||||||
assert self.str_cap_limit_prob_type in ['uniform', 'normal'], \
|
assert self.str_cap_limit_prob_type in ['uniform', 'normal'], \
|
||||||
"cap_limit_prob_type other than uniform, normal"
|
"cap_limit_prob_type other than uniform, normal"
|
||||||
if self.str_cap_limit_prob_type == 'uniform':
|
if self.str_cap_limit_prob_type == 'uniform':
|
||||||
|
@ -52,59 +54,73 @@ class FirmAgent(ap.Agent):
|
||||||
extra_cap = self.model.nprandom.integers(extra_cap_mean-2,
|
extra_cap = self.model.nprandom.integers(extra_cap_mean-2,
|
||||||
extra_cap_mean+2)
|
extra_cap_mean+2)
|
||||||
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
||||||
# print(firm_agent.name, extra_cap)
|
|
||||||
self.dct_prod_capacity[product] = extra_cap
|
self.dct_prod_capacity[product] = extra_cap
|
||||||
elif self.str_cap_limit_prob_type == 'normal':
|
elif self.str_cap_limit_prob_type == 'normal':
|
||||||
extra_cap_mean = \
|
extra_cap_mean = \
|
||||||
self.size_stat[0][0] / self.flt_cap_limit_level
|
self.size_stat[0][0] / self.flt_cap_limit_level
|
||||||
extra_cap = self.model.nprandom.normal(extra_cap_mean, 1)
|
extra_cap = self.model.nprandom.normal(extra_cap_mean, 1)
|
||||||
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
||||||
# print(firm_agent.name, extra_cap)
|
|
||||||
self.dct_prod_capacity[product] = extra_cap
|
self.dct_prod_capacity[product] = extra_cap
|
||||||
|
|
||||||
def remove_edge_to_cus_disrupt_cus_up_prod(self, disrupted_prod):
|
def remove_edge_to_cus(self, disrupted_prod):
|
||||||
# para disrupted_prod is the product that self got disrupted
|
# parameter disrupted_prod is the product that self got disrupted
|
||||||
lst_out_edge = list(
|
lst_out_edge = list(
|
||||||
self.firm_network.graph.out_edges(
|
self.firm_network.graph.out_edges(
|
||||||
self.firm_network.positions[self], keys=True, data='Product'))
|
self.firm_network.positions[self], keys=True, data='Product'))
|
||||||
for n1, n2, key, product_code in lst_out_edge:
|
for n1, n2, key, product_code in lst_out_edge:
|
||||||
if product_code == disrupted_prod.code:
|
if product_code == disrupted_prod.code:
|
||||||
|
# update customer up product supplier status
|
||||||
|
customer = ap.AgentIter(self.model, n2).to_list()[0]
|
||||||
|
for prod in customer.dct_prod_up_prod_stat.keys():
|
||||||
|
if disrupted_prod in \
|
||||||
|
customer.dct_prod_up_prod_stat[
|
||||||
|
prod]['s_stat'].keys():
|
||||||
|
customer.dct_prod_up_prod_stat[
|
||||||
|
prod]['s_stat'][disrupted_prod][
|
||||||
|
'set_disrupt_firm'].add(self)
|
||||||
|
# print(f"{self.name} disrupt {customer.name}'s "
|
||||||
|
# f"{prod.code} due to {disrupted_prod.code}")
|
||||||
# remove edge to customer
|
# remove edge to customer
|
||||||
self.firm_network.graph.remove_edge(n1, n2, key)
|
self.firm_network.graph.remove_edge(n1, n2, key)
|
||||||
|
|
||||||
# customer up product affected conditionally
|
def disrupt_cus_prod(self, prod, disrupted_up_prod):
|
||||||
customer = ap.AgentIter(self.model, n2).to_list()[0]
|
# parameter prod is the product that has disrupted_up_prod
|
||||||
lst_in_edge = list(
|
# parameter disrupted_up_prod is the product that
|
||||||
self.firm_network.graph.in_edges(n2,
|
# self's component exists disrupted supplier
|
||||||
keys=True,
|
num_lost = \
|
||||||
data='Product'))
|
len(self.dct_prod_up_prod_stat[prod]['s_stat']
|
||||||
lst_select_in_edge = [
|
[disrupted_up_prod]['set_disrupt_firm'])
|
||||||
edge for edge in lst_in_edge
|
num_remain = \
|
||||||
if edge[-1] == disrupted_prod.code
|
len([u for u, _, _, d in
|
||||||
]
|
self.firm_network.graph.in_edges(self.get_firm_network_node(),
|
||||||
prob_lost_supp = math.exp(-1 * self.flt_crit_supplier *
|
keys=True,
|
||||||
len(lst_select_in_edge))
|
data='Product')
|
||||||
if self.model.nprandom.choice([True, False],
|
if d == disrupted_up_prod.code])
|
||||||
p=[prob_lost_supp,
|
lost_percent = num_lost / (num_lost + num_remain)
|
||||||
1 - prob_lost_supp]):
|
lst_size = \
|
||||||
customer.dct_n_trial_up_prod_disrupted[disrupted_prod] = 0
|
[firm.size_stat[-1][0] for firm in self.model.a_lst_total_firms]
|
||||||
for prod in customer.dct_prod_up_prod_stat.keys():
|
std_size = (self.size_stat[-1][0] - min(lst_size) + 1) \
|
||||||
if disrupted_prod in \
|
/ (max(lst_size) - min(lst_size) + 1)
|
||||||
customer.dct_prod_up_prod_stat[
|
|
||||||
prod]['supply'].keys():
|
# calculate probability of disruption
|
||||||
customer.dct_prod_up_prod_stat[
|
prob_disrupt = 1 - std_size * (1 - lost_percent)
|
||||||
prod]['supply'][disrupted_prod] = False
|
if self.model.nprandom.choice([True, False],
|
||||||
status, _ = customer.dct_prod_up_prod_stat[
|
p=[prob_disrupt,
|
||||||
prod]['status'][-1]
|
1 - prob_disrupt]):
|
||||||
if status != 'D':
|
self.dct_n_trial_up_prod_disrupted[disrupted_up_prod] = 0
|
||||||
customer.dct_prod_up_prod_stat[
|
self.dct_prod_up_prod_stat[
|
||||||
prod]['status'].append(('D', self.model.t))
|
prod]['s_stat'][disrupted_up_prod]['stat'] = False
|
||||||
print(self.name, disrupted_prod.code, 'disrupt',
|
status, _ = self.dct_prod_up_prod_stat[
|
||||||
customer.name, prod.code)
|
prod]['p_stat'][-1]
|
||||||
|
if status != 'D':
|
||||||
|
self.dct_prod_up_prod_stat[
|
||||||
|
prod]['p_stat'].append(('D', self.model.t))
|
||||||
|
# print(f"{self.name}'s {prod.code} turn to D status due to "
|
||||||
|
# f"disrupted supplier of {disrupted_up_prod.code}")
|
||||||
|
|
||||||
def seek_alt_supply(self, product):
|
def seek_alt_supply(self, product):
|
||||||
# para product is the product that self is seeking
|
# parameter product is the product that self is seeking
|
||||||
print(f"{self.name} seek alt supply for {product.code}")
|
# print(f"{self.name} seek alt supply for {product.code}")
|
||||||
if self.dct_n_trial_up_prod_disrupted[
|
if self.dct_n_trial_up_prod_disrupted[
|
||||||
product] <= self.model.int_n_max_trial:
|
product] <= self.model.int_n_max_trial:
|
||||||
if self.dct_n_trial_up_prod_disrupted[product] == 0:
|
if self.dct_n_trial_up_prod_disrupted[product] == 0:
|
||||||
|
@ -120,18 +136,12 @@ class FirmAgent(ap.Agent):
|
||||||
if self.is_prf_conn:
|
if self.is_prf_conn:
|
||||||
for firm in \
|
for firm in \
|
||||||
self.dct_cand_alt_supp_up_prod_disrupted[product]:
|
self.dct_cand_alt_supp_up_prod_disrupted[product]:
|
||||||
out_edges = self.model.firm_network.graph.out_edges(
|
node_self = self.get_firm_network_node()
|
||||||
self.model.firm_network.positions[firm], keys=True)
|
node_firm = firm.get_firm_network_node()
|
||||||
in_edges = self.model.firm_network.graph.in_edges(
|
if self.model.firm_network.graph.\
|
||||||
self.model.firm_network.positions[firm], keys=True)
|
has_edge(node_self, node_firm) or \
|
||||||
lst_adj_firm = []
|
self.model.firm_network.graph.\
|
||||||
lst_adj_firm += \
|
has_edge(node_firm, node_self):
|
||||||
[ap.AgentIter(self.model, edge[1]).to_list()[
|
|
||||||
0].code for edge in out_edges]
|
|
||||||
lst_adj_firm += \
|
|
||||||
[ap.AgentIter(self.model, edge[0]).to_list()[
|
|
||||||
0].code for edge in in_edges]
|
|
||||||
if self.code in lst_adj_firm:
|
|
||||||
lst_firm_connect.append(firm)
|
lst_firm_connect.append(firm)
|
||||||
if len(lst_firm_connect) == 0:
|
if len(lst_firm_connect) == 0:
|
||||||
# select based on size or not
|
# select based on size or not
|
||||||
|
@ -163,10 +173,10 @@ class FirmAgent(ap.Agent):
|
||||||
else:
|
else:
|
||||||
select_alt_supply = \
|
select_alt_supply = \
|
||||||
self.model.nprandom.choice(lst_firm_connect)
|
self.model.nprandom.choice(lst_firm_connect)
|
||||||
print(
|
# print(
|
||||||
f"{self.name} selct alt supply for {product.code} "
|
# f"{self.name} selct alt supply for {product.code} "
|
||||||
f"from {select_alt_supply.name}"
|
# f"from {select_alt_supply.name}"
|
||||||
)
|
# )
|
||||||
assert select_alt_supply.is_prod_in_current_normal(product), \
|
assert select_alt_supply.is_prod_in_current_normal(product), \
|
||||||
f"{select_alt_supply} \
|
f"{select_alt_supply} \
|
||||||
does not produce requested product {product}"
|
does not produce requested product {product}"
|
||||||
|
@ -179,17 +189,17 @@ class FirmAgent(ap.Agent):
|
||||||
select_alt_supply.dct_request_prod_from_firm[product] = [
|
select_alt_supply.dct_request_prod_from_firm[product] = [
|
||||||
self
|
self
|
||||||
]
|
]
|
||||||
print(
|
# print(
|
||||||
select_alt_supply.name, 'dct_request_prod_from_firm', {
|
# select_alt_supply.name, 'dct_request_prod_from_firm', {
|
||||||
key.code: [v.name for v in value]
|
# key.code: [v.name for v in value]
|
||||||
for key, value in
|
# for key, value in
|
||||||
select_alt_supply.dct_request_prod_from_firm.items()
|
# select_alt_supply.dct_request_prod_from_firm.items()
|
||||||
})
|
# })
|
||||||
|
|
||||||
self.dct_n_trial_up_prod_disrupted[product] += 1
|
self.dct_n_trial_up_prod_disrupted[product] += 1
|
||||||
|
|
||||||
def handle_request(self):
|
def handle_request(self):
|
||||||
print(self.name, 'handle_request')
|
# print(self.name, 'handle_request')
|
||||||
for product, lst_firm in self.dct_request_prod_from_firm.items():
|
for product, lst_firm in self.dct_request_prod_from_firm.items():
|
||||||
if self.dct_prod_capacity[product] > 0:
|
if self.dct_prod_capacity[product] > 0:
|
||||||
if len(lst_firm) == 0:
|
if len(lst_firm) == 0:
|
||||||
|
@ -201,22 +211,12 @@ class FirmAgent(ap.Agent):
|
||||||
lst_firm_connect = []
|
lst_firm_connect = []
|
||||||
if self.is_prf_conn:
|
if self.is_prf_conn:
|
||||||
for firm in lst_firm:
|
for firm in lst_firm:
|
||||||
out_edges = \
|
node_self = self.get_firm_network_node()
|
||||||
self.model.firm_network.graph.out_edges(
|
node_firm = firm.get_firm_network_node()
|
||||||
self.model.firm_network.positions[firm],
|
if self.model.firm_network.graph.\
|
||||||
keys=True)
|
has_edge(node_self, node_firm) or \
|
||||||
in_edges = \
|
self.model.firm_network.graph.\
|
||||||
self.model.firm_network.graph.in_edges(
|
has_edge(node_firm, node_self):
|
||||||
self.model.firm_network.positions[firm],
|
|
||||||
keys=True)
|
|
||||||
lst_adj_firm = []
|
|
||||||
lst_adj_firm += \
|
|
||||||
[ap.AgentIter(self.model, edge[1]).to_list()[
|
|
||||||
0].code for edge in out_edges]
|
|
||||||
lst_adj_firm += \
|
|
||||||
[ap.AgentIter(self.model, edge[0]).to_list()[
|
|
||||||
0].code for edge in in_edges]
|
|
||||||
if self.code in lst_adj_firm:
|
|
||||||
lst_firm_connect.append(firm)
|
lst_firm_connect.append(firm)
|
||||||
if len(lst_firm_connect) == 0:
|
if len(lst_firm_connect) == 0:
|
||||||
# handling based on size or not
|
# handling based on size or not
|
||||||
|
@ -254,14 +254,21 @@ class FirmAgent(ap.Agent):
|
||||||
down_firm.dct_cand_alt_supp_up_prod_disrupted[
|
down_firm.dct_cand_alt_supp_up_prod_disrupted[
|
||||||
product].remove(self)
|
product].remove(self)
|
||||||
|
|
||||||
print(
|
# print(
|
||||||
f"{self.name} denied {product.code} request "
|
# f"{self.name} denied {product.code} request "
|
||||||
f"from {down_firm.name} for lack of capacity"
|
# f"from {down_firm.name} for lack of capacity"
|
||||||
)
|
# )
|
||||||
|
|
||||||
def accept_request(self, down_firm, product):
|
def accept_request(self, down_firm, product):
|
||||||
# para product is the product that self is selling
|
# parameter product is the product that self is selling
|
||||||
prod_accept = self.flt_diff_new_conn
|
# connected firm has no probability for accepting request
|
||||||
|
node_self = self.get_firm_network_node()
|
||||||
|
node_d_firm = down_firm.get_firm_network_node()
|
||||||
|
if self.model.firm_network.graph.has_edge(node_self, node_d_firm) or \
|
||||||
|
self.model.firm_network.graph.has_edge(node_d_firm, node_self):
|
||||||
|
prod_accept = 1.0
|
||||||
|
else:
|
||||||
|
prod_accept = self.flt_diff_new_conn
|
||||||
if self.model.nprandom.choice([True, False],
|
if self.model.nprandom.choice([True, False],
|
||||||
p=[prod_accept, 1 - prod_accept]):
|
p=[prod_accept, 1 - prod_accept]):
|
||||||
self.firm_network.graph.add_edges_from([
|
self.firm_network.graph.add_edges_from([
|
||||||
|
@ -275,25 +282,25 @@ class FirmAgent(ap.Agent):
|
||||||
|
|
||||||
for prod in down_firm.dct_prod_up_prod_stat.keys():
|
for prod in down_firm.dct_prod_up_prod_stat.keys():
|
||||||
if product in down_firm.dct_prod_up_prod_stat[
|
if product in down_firm.dct_prod_up_prod_stat[
|
||||||
prod]['supply'].keys():
|
prod]['s_stat'].keys():
|
||||||
down_firm.dct_prod_up_prod_stat[
|
down_firm.dct_prod_up_prod_stat[
|
||||||
prod]['supply'][product] = True
|
prod]['s_stat'][product]['stat'] = True
|
||||||
down_firm.dct_prod_up_prod_stat[
|
down_firm.dct_prod_up_prod_stat[
|
||||||
prod]['status'].append(('N', self.model.t))
|
prod]['p_stat'].append(('N', self.model.t))
|
||||||
del down_firm.dct_n_trial_up_prod_disrupted[product]
|
del down_firm.dct_n_trial_up_prod_disrupted[product]
|
||||||
del down_firm.dct_cand_alt_supp_up_prod_disrupted[product]
|
del down_firm.dct_cand_alt_supp_up_prod_disrupted[product]
|
||||||
|
|
||||||
print(
|
# print(
|
||||||
f"{self.name} accept {product.code} request "
|
# f"{self.name} accept {product.code} request "
|
||||||
f"from {down_firm.name}"
|
# f"from {down_firm.name}"
|
||||||
)
|
# )
|
||||||
else:
|
else:
|
||||||
down_firm.dct_cand_alt_supp_up_prod_disrupted[product].remove(self)
|
down_firm.dct_cand_alt_supp_up_prod_disrupted[product].remove(self)
|
||||||
|
|
||||||
print(
|
# print(
|
||||||
f"{self.name} denied {product.code} request "
|
# f"{self.name} denied {product.code} request "
|
||||||
f"from {down_firm.name}"
|
# f"from {down_firm.name}"
|
||||||
)
|
# )
|
||||||
|
|
||||||
def clean_before_trial(self):
|
def clean_before_trial(self):
|
||||||
self.dct_request_prod_from_firm = {}
|
self.dct_request_prod_from_firm = {}
|
||||||
|
@ -305,17 +312,21 @@ class FirmAgent(ap.Agent):
|
||||||
|
|
||||||
# update the status of firm
|
# update the status of firm
|
||||||
for prod in self.dct_prod_up_prod_stat.keys():
|
for prod in self.dct_prod_up_prod_stat.keys():
|
||||||
status, ts = self.dct_prod_up_prod_stat[prod]['status'][-1]
|
status, ts = self.dct_prod_up_prod_stat[prod]['p_stat'][-1]
|
||||||
if ts != self.model.t:
|
if ts != self.model.t:
|
||||||
self.dct_prod_up_prod_stat[prod]['status'].append(
|
self.dct_prod_up_prod_stat[prod]['p_stat'].append(
|
||||||
(status, self.model.t))
|
(status, self.model.t))
|
||||||
|
# refresh set_disrupt_firm
|
||||||
|
for up_prod in self.dct_prod_up_prod_stat[prod]['s_stat'].keys():
|
||||||
|
self.dct_prod_up_prod_stat[prod][
|
||||||
|
's_stat'][up_prod]['set_disrupt_firm'] = set()
|
||||||
|
|
||||||
def get_firm_network_node(self):
|
def get_firm_network_node(self):
|
||||||
return self.firm_network.positions[self]
|
return self.firm_network.positions[self]
|
||||||
|
|
||||||
def is_prod_in_current_normal(self, prod):
|
def is_prod_in_current_normal(self, prod):
|
||||||
if prod in self.dct_prod_up_prod_stat.keys():
|
if prod in self.dct_prod_up_prod_stat.keys():
|
||||||
if self.dct_prod_up_prod_stat[prod]['status'][-1][0] == 'N':
|
if self.dct_prod_up_prod_stat[prod]['p_stat'][-1][0] == 'N':
|
||||||
return True
|
return True
|
||||||
else:
|
else:
|
||||||
return False
|
return False
|
||||||
|
|
|
@ -0,0 +1,172 @@
|
||||||
|
code,n_prod
|
||||||
|
0,1
|
||||||
|
1,1
|
||||||
|
2,1
|
||||||
|
3,4
|
||||||
|
4,1
|
||||||
|
5,4
|
||||||
|
6,5
|
||||||
|
7,1
|
||||||
|
8,1
|
||||||
|
9,2
|
||||||
|
10,1
|
||||||
|
11,1
|
||||||
|
12,1
|
||||||
|
13,17
|
||||||
|
14,2
|
||||||
|
15,1
|
||||||
|
16,4
|
||||||
|
17,1
|
||||||
|
18,1
|
||||||
|
19,1
|
||||||
|
20,1
|
||||||
|
21,1
|
||||||
|
22,24
|
||||||
|
23,10
|
||||||
|
24,1
|
||||||
|
25,1
|
||||||
|
26,7
|
||||||
|
27,1
|
||||||
|
28,1
|
||||||
|
29,1
|
||||||
|
30,1
|
||||||
|
31,7
|
||||||
|
32,1
|
||||||
|
33,4
|
||||||
|
34,1
|
||||||
|
35,1
|
||||||
|
36,1
|
||||||
|
37,6
|
||||||
|
38,5
|
||||||
|
39,1
|
||||||
|
40,4
|
||||||
|
41,7
|
||||||
|
42,3
|
||||||
|
43,2
|
||||||
|
44,1
|
||||||
|
45,9
|
||||||
|
46,1
|
||||||
|
47,9
|
||||||
|
48,1
|
||||||
|
49,8
|
||||||
|
50,1
|
||||||
|
51,1
|
||||||
|
52,1
|
||||||
|
53,15
|
||||||
|
54,3
|
||||||
|
55,6
|
||||||
|
56,2
|
||||||
|
57,4
|
||||||
|
58,7
|
||||||
|
59,1
|
||||||
|
60,5
|
||||||
|
61,1
|
||||||
|
62,5
|
||||||
|
63,3
|
||||||
|
64,1
|
||||||
|
65,1
|
||||||
|
66,1
|
||||||
|
67,1
|
||||||
|
68,3
|
||||||
|
69,1
|
||||||
|
70,2
|
||||||
|
71,1
|
||||||
|
72,1
|
||||||
|
73,1
|
||||||
|
74,2
|
||||||
|
75,1
|
||||||
|
76,1
|
||||||
|
77,2
|
||||||
|
78,5
|
||||||
|
79,16
|
||||||
|
80,2
|
||||||
|
81,4
|
||||||
|
82,4
|
||||||
|
83,1
|
||||||
|
84,3
|
||||||
|
85,2
|
||||||
|
86,1
|
||||||
|
87,1
|
||||||
|
88,1
|
||||||
|
89,3
|
||||||
|
90,1
|
||||||
|
91,1
|
||||||
|
92,1
|
||||||
|
93,1
|
||||||
|
94,1
|
||||||
|
95,2
|
||||||
|
96,2
|
||||||
|
97,3
|
||||||
|
98,1
|
||||||
|
99,6
|
||||||
|
100,1
|
||||||
|
101,1
|
||||||
|
102,2
|
||||||
|
103,1
|
||||||
|
104,1
|
||||||
|
105,1
|
||||||
|
106,6
|
||||||
|
107,1
|
||||||
|
108,2
|
||||||
|
109,1
|
||||||
|
110,1
|
||||||
|
111,3
|
||||||
|
112,1
|
||||||
|
113,1
|
||||||
|
114,1
|
||||||
|
115,2
|
||||||
|
116,1
|
||||||
|
117,11
|
||||||
|
118,1
|
||||||
|
119,1
|
||||||
|
120,1
|
||||||
|
121,1
|
||||||
|
122,1
|
||||||
|
123,1
|
||||||
|
124,2
|
||||||
|
125,1
|
||||||
|
126,7
|
||||||
|
127,2
|
||||||
|
128,1
|
||||||
|
129,2
|
||||||
|
130,5
|
||||||
|
131,5
|
||||||
|
132,1
|
||||||
|
133,2
|
||||||
|
134,1
|
||||||
|
135,11
|
||||||
|
136,1
|
||||||
|
137,6
|
||||||
|
138,1
|
||||||
|
139,1
|
||||||
|
140,7
|
||||||
|
141,1
|
||||||
|
142,3
|
||||||
|
143,5
|
||||||
|
144,4
|
||||||
|
145,1
|
||||||
|
146,1
|
||||||
|
147,1
|
||||||
|
148,3
|
||||||
|
149,4
|
||||||
|
150,1
|
||||||
|
151,1
|
||||||
|
152,1
|
||||||
|
153,2
|
||||||
|
154,6
|
||||||
|
155,1
|
||||||
|
156,1
|
||||||
|
157,1
|
||||||
|
158,1
|
||||||
|
159,1
|
||||||
|
160,1
|
||||||
|
161,3
|
||||||
|
162,2
|
||||||
|
163,6
|
||||||
|
164,1
|
||||||
|
165,4
|
||||||
|
166,1
|
||||||
|
167,1
|
||||||
|
168,7
|
||||||
|
169,1
|
||||||
|
170,1
|
|
295
model.py
|
@ -10,7 +10,7 @@ import json
|
||||||
|
|
||||||
class Model(ap.Model):
|
class Model(ap.Model):
|
||||||
def setup(self):
|
def setup(self):
|
||||||
# self para
|
# self parameter
|
||||||
self.sample = self.p.sample
|
self.sample = self.p.sample
|
||||||
self.int_stop_ts = 0
|
self.int_stop_ts = 0
|
||||||
self.int_n_iter = int(self.p.n_iter)
|
self.int_n_iter = int(self.p.n_iter)
|
||||||
|
@ -23,15 +23,15 @@ class Model(ap.Model):
|
||||||
# external variable
|
# external variable
|
||||||
self.int_n_max_trial = int(self.p.n_max_trial)
|
self.int_n_max_trial = int(self.p.n_max_trial)
|
||||||
self.is_prf_size = bool(self.p.prf_size)
|
self.is_prf_size = bool(self.p.prf_size)
|
||||||
self.proactive_ratio = float(self.p.proactive_ratio)
|
# self.proactive_ratio = float(self.p.proactive_ratio) # dropped
|
||||||
self.remove_t = int(self.p.remove_t)
|
self.remove_t = int(self.p.remove_t)
|
||||||
self.int_netw_prf_n = int(self.p.netw_prf_n)
|
self.int_netw_prf_n = int(self.p.netw_prf_n)
|
||||||
|
|
||||||
# init graph bom
|
# initialize graph bom
|
||||||
G_bom = nx.adjacency_graph(json.loads(self.p.g_bom))
|
G_bom = nx.adjacency_graph(json.loads(self.p.g_bom))
|
||||||
self.product_network = ap.Network(self, G_bom)
|
self.product_network = ap.Network(self, G_bom)
|
||||||
|
|
||||||
# init graph firm
|
# initialize graph firm
|
||||||
Firm = pd.read_csv("Firm_amended.csv")
|
Firm = pd.read_csv("Firm_amended.csv")
|
||||||
Firm['Code'] = Firm['Code'].astype('string')
|
Firm['Code'] = Firm['Code'].astype('string')
|
||||||
Firm.fillna(0, inplace=True)
|
Firm.fillna(0, inplace=True)
|
||||||
|
@ -49,7 +49,7 @@ class Model(ap.Model):
|
||||||
firm_labels_dict[code] = Firm_attr.loc[code].to_dict()
|
firm_labels_dict[code] = Firm_attr.loc[code].to_dict()
|
||||||
nx.set_node_attributes(G_Firm, firm_labels_dict)
|
nx.set_node_attributes(G_Firm, firm_labels_dict)
|
||||||
|
|
||||||
# init graph firm prod
|
# initialize graph firm prod
|
||||||
Firm_Prod = pd.read_csv("Firm_amended.csv")
|
Firm_Prod = pd.read_csv("Firm_amended.csv")
|
||||||
Firm_Prod.fillna(0, inplace=True)
|
Firm_Prod.fillna(0, inplace=True)
|
||||||
firm_prod = pd.DataFrame({'bool': Firm_Prod.loc[:, '1':].stack()})
|
firm_prod = pd.DataFrame({'bool': Firm_Prod.loc[:, '1':].stack()})
|
||||||
|
@ -122,11 +122,12 @@ class Model(ap.Model):
|
||||||
# nx.to_pandas_adjacency(G_Firm).to_csv('adj_g_firm.csv')
|
# nx.to_pandas_adjacency(G_Firm).to_csv('adj_g_firm.csv')
|
||||||
# nx.to_pandas_adjacency(G_FirmProd).to_csv('adj_g_firm_prod.csv')
|
# nx.to_pandas_adjacency(G_FirmProd).to_csv('adj_g_firm_prod.csv')
|
||||||
|
|
||||||
# unconnected node
|
# connect unconnected nodes
|
||||||
for node in nx.nodes(G_Firm):
|
for node in nx.nodes(G_Firm):
|
||||||
if G_Firm.degree(node) == 0:
|
if G_Firm.degree(node) == 0:
|
||||||
for product_code in G_Firm.nodes[node]['Product_Code']:
|
for product_code in G_Firm.nodes[node]['Product_Code']:
|
||||||
# unconnect node does not have possible suppliers
|
# unconnected node does not have possible suppliers,
|
||||||
|
# therefore find possible customer instead
|
||||||
# current node in graph firm prod
|
# current node in graph firm prod
|
||||||
current_node = \
|
current_node = \
|
||||||
[n for n, v in G_FirmProd.nodes(data=True)
|
[n for n, v in G_FirmProd.nodes(data=True)
|
||||||
|
@ -135,10 +136,10 @@ class Model(ap.Model):
|
||||||
|
|
||||||
lst_succ_product_code = list(
|
lst_succ_product_code = list(
|
||||||
G_bom.successors(product_code))
|
G_bom.successors(product_code))
|
||||||
# different from for different types of product,
|
# different from: for different types of product,
|
||||||
# finding a common supplier (the logic above),
|
# finding a common supplier (the logic above),
|
||||||
# for different types of product,
|
# instead: for different types of product,
|
||||||
# finding a custormer for each product
|
# finding a customer for each product
|
||||||
for succ_product_code in lst_succ_product_code:
|
for succ_product_code in lst_succ_product_code:
|
||||||
# for each product successor (finished product)
|
# for each product successor (finished product)
|
||||||
# the firm sells to,
|
# the firm sells to,
|
||||||
|
@ -187,14 +188,14 @@ class Model(ap.Model):
|
||||||
# nx.draw(G_FirmProd)
|
# nx.draw(G_FirmProd)
|
||||||
# plt.show()
|
# plt.show()
|
||||||
|
|
||||||
# init product
|
# initialize product
|
||||||
for ag_node, attr in self.product_network.graph.nodes(data=True):
|
for ag_node, attr in self.product_network.graph.nodes(data=True):
|
||||||
product = ProductAgent(self, code=ag_node.label, name=attr['Name'])
|
product = ProductAgent(self, code=ag_node.label, name=attr['Name'])
|
||||||
self.product_network.add_agents([product], [ag_node])
|
self.product_network.add_agents([product], [ag_node])
|
||||||
self.a_lst_total_products = ap.AgentList(self,
|
self.a_lst_total_products = ap.AgentList(self,
|
||||||
self.product_network.agents)
|
self.product_network.agents)
|
||||||
|
|
||||||
# init firm
|
# initialize firm
|
||||||
for ag_node, attr in self.firm_network.graph.nodes(data=True):
|
for ag_node, attr in self.firm_network.graph.nodes(data=True):
|
||||||
firm_agent = FirmAgent(
|
firm_agent = FirmAgent(
|
||||||
self,
|
self,
|
||||||
|
@ -210,7 +211,7 @@ class Model(ap.Model):
|
||||||
self.firm_network.add_agents([firm_agent], [ag_node])
|
self.firm_network.add_agents([firm_agent], [ag_node])
|
||||||
self.a_lst_total_firms = ap.AgentList(self, self.firm_network.agents)
|
self.a_lst_total_firms = ap.AgentList(self, self.firm_network.agents)
|
||||||
|
|
||||||
# init dct_lst_init_disrupt_firm_prod (from string to agent)
|
# initialize dct_lst_init_disrupt_firm_prod (from string to agent)
|
||||||
t_dct = {}
|
t_dct = {}
|
||||||
for firm_code, lst_product in \
|
for firm_code, lst_product in \
|
||||||
self.dct_lst_init_disrupt_firm_prod.items():
|
self.dct_lst_init_disrupt_firm_prod.items():
|
||||||
|
@ -222,123 +223,123 @@ class Model(ap.Model):
|
||||||
self.dct_lst_init_disrupt_firm_prod = t_dct
|
self.dct_lst_init_disrupt_firm_prod = t_dct
|
||||||
|
|
||||||
# set the initial firm product that are disrupted
|
# set the initial firm product that are disrupted
|
||||||
print('\n', '=' * 20, 'step', self.t, '=' * 20)
|
# print('\n', '=' * 20, 'step', self.t, '=' * 20)
|
||||||
for firm, a_lst_product in self.dct_lst_init_disrupt_firm_prod.items():
|
for firm, a_lst_product in self.dct_lst_init_disrupt_firm_prod.items():
|
||||||
for product in a_lst_product:
|
for product in a_lst_product:
|
||||||
assert product in firm.dct_prod_up_prod_stat.keys(), \
|
assert product in firm.dct_prod_up_prod_stat.keys(), \
|
||||||
f"product {product.code} not in firm {firm.code}"
|
f"product {product.code} not in firm {firm.code}"
|
||||||
firm.dct_prod_up_prod_stat[
|
firm.dct_prod_up_prod_stat[
|
||||||
product]['status'].append(('D', self.t))
|
product]['p_stat'].append(('D', self.t))
|
||||||
print(f"initial disruption {firm.name} {product.code}")
|
# print(f"initial disruption {firm.name} {product.code}")
|
||||||
|
|
||||||
# proactive strategy
|
# # proactive strategy (dropped)
|
||||||
# get all the firm prod affected
|
# # get all the firm prod affected
|
||||||
for firm, a_lst_product in self.dct_lst_init_disrupt_firm_prod.items():
|
# for firm, a_lst_product in self.dct_lst_init_disrupt_firm_prod.items():
|
||||||
for product in a_lst_product:
|
# for product in a_lst_product:
|
||||||
init_node = \
|
# init_node = \
|
||||||
[n for n, v in
|
# [n for n, v in
|
||||||
self.firm_prod_network.nodes(data=True)
|
# self.firm_prod_network.nodes(data=True)
|
||||||
if v['Firm_Code'] == firm.code and
|
# if v['Firm_Code'] == firm.code and
|
||||||
v['Product_Code'] == product.code][0]
|
# v['Product_Code'] == product.code][0]
|
||||||
dct_affected = \
|
# dct_affected = \
|
||||||
nx.dfs_successors(self.firm_prod_network,
|
# nx.dfs_successors(self.firm_prod_network,
|
||||||
init_node)
|
# init_node)
|
||||||
lst_affected = set()
|
# lst_affected = set()
|
||||||
for i, (u, vs) in enumerate(dct_affected.items()):
|
# for i, (u, vs) in enumerate(dct_affected.items()):
|
||||||
# at least 2 hops away
|
# # at least 2 hops away
|
||||||
if i > 0:
|
# if i > 0:
|
||||||
pred_node = self.firm_prod_network.nodes[u]
|
# pred_node = self.firm_prod_network.nodes[u]
|
||||||
for v in vs:
|
# for v in vs:
|
||||||
succ_node = self.firm_prod_network.nodes[v]
|
# succ_node = self.firm_prod_network.nodes[v]
|
||||||
lst_affected.add((succ_node['Firm_Code'],
|
# lst_affected.add((succ_node['Firm_Code'],
|
||||||
succ_node['Product_Code']))
|
# succ_node['Product_Code']))
|
||||||
lst_affected = list(lst_affected)
|
# lst_affected = list(lst_affected)
|
||||||
lst_firm_proactive = \
|
# lst_firm_proactive = \
|
||||||
[lst_affected[i] for i in
|
# [lst_affected[i] for i in
|
||||||
self.nprandom.choice(range(len(lst_affected)),
|
# self.nprandom.choice(range(len(lst_affected)),
|
||||||
round(len(lst_affected) *
|
# round(len(lst_affected) *
|
||||||
self.proactive_ratio),
|
# self.proactive_ratio),
|
||||||
replace=False)]
|
# replace=False)]
|
||||||
|
|
||||||
for firm_code, prod_code in lst_firm_proactive:
|
# for firm_code, prod_code in lst_firm_proactive:
|
||||||
pro_firm_prod_code = \
|
# pro_firm_prod_code = \
|
||||||
[n for n, v in
|
# [n for n, v in
|
||||||
self.firm_prod_network.nodes(data=True)
|
# self.firm_prod_network.nodes(data=True)
|
||||||
if v['Firm_Code'] == firm_code and
|
# if v['Firm_Code'] == firm_code and
|
||||||
v['Product_Code'] == prod_code][0]
|
# v['Product_Code'] == prod_code][0]
|
||||||
pro_firm_prod_node = \
|
# pro_firm_prod_node = \
|
||||||
self.firm_prod_network.nodes[pro_firm_prod_code]
|
# self.firm_prod_network.nodes[pro_firm_prod_code]
|
||||||
pro_firm = \
|
# pro_firm = \
|
||||||
self.a_lst_total_firms.select(
|
# self.a_lst_total_firms.select(
|
||||||
[firm.code == pro_firm_prod_node['Firm_Code']
|
# [firm.code == pro_firm_prod_node['Firm_Code']
|
||||||
for firm in self.a_lst_total_firms])[0]
|
# for firm in self.a_lst_total_firms])[0]
|
||||||
lst_shortest_path = \
|
# lst_shortest_path = \
|
||||||
list(nx.all_shortest_paths(self.firm_prod_network,
|
# list(nx.all_shortest_paths(self.firm_prod_network,
|
||||||
source=init_node,
|
# source=init_node,
|
||||||
target=pro_firm_prod_code))
|
# target=pro_firm_prod_code))
|
||||||
|
|
||||||
dct_drs = {}
|
# dct_drs = {}
|
||||||
for di_supp_code in self.firm_prod_network.predecessors(
|
# for di_supp_code in self.firm_prod_network.predecessors(
|
||||||
pro_firm_prod_code):
|
# pro_firm_prod_code):
|
||||||
di_supp_node = \
|
# di_supp_node = \
|
||||||
self.firm_prod_network.nodes[di_supp_code]
|
# self.firm_prod_network.nodes[di_supp_code]
|
||||||
di_supp_prod = \
|
# di_supp_prod = \
|
||||||
self.a_lst_total_products.select(
|
# self.a_lst_total_products.select(
|
||||||
[product.code == di_supp_node['Product_Code']
|
# [product.code == di_supp_node['Product_Code']
|
||||||
for product in self.a_lst_total_products])[0]
|
# for product in self.a_lst_total_products])[0]
|
||||||
di_supp_firm = \
|
# di_supp_firm = \
|
||||||
self.a_lst_total_firms.select(
|
# self.a_lst_total_firms.select(
|
||||||
[firm.code == di_supp_node['Firm_Code']
|
# [firm.code == di_supp_node['Firm_Code']
|
||||||
for firm in self.a_lst_total_firms])[0]
|
# for firm in self.a_lst_total_firms])[0]
|
||||||
lst_cand = self.a_lst_total_firms.select([
|
# lst_cand = self.a_lst_total_firms.select([
|
||||||
firm.is_prod_in_current_normal(di_supp_prod)
|
# firm.is_prod_in_current_normal(di_supp_prod)
|
||||||
for firm in self.a_lst_total_firms
|
# for firm in self.a_lst_total_firms
|
||||||
])
|
# ])
|
||||||
n2n_betweenness = \
|
# n2n_betweenness = \
|
||||||
sum([True if di_supp_code in path else False
|
# sum([True if di_supp_code in path else False
|
||||||
for path in lst_shortest_path]) \
|
# for path in lst_shortest_path]) \
|
||||||
/ len(lst_shortest_path)
|
# / len(lst_shortest_path)
|
||||||
drs = n2n_betweenness / \
|
# drs = n2n_betweenness / \
|
||||||
(len(lst_cand) * di_supp_firm.size_stat[-1][0])
|
# (len(lst_cand) * di_supp_firm.size_stat[-1][0])
|
||||||
dct_drs[di_supp_code] = drs
|
# dct_drs[di_supp_code] = drs
|
||||||
dct_drs = dict(sorted(
|
# dct_drs = dict(sorted(
|
||||||
dct_drs.items(), key=lambda kv: kv[1], reverse=True))
|
# dct_drs.items(), key=lambda kv: kv[1], reverse=True))
|
||||||
for di_supp_code in dct_drs.keys():
|
# for di_supp_code in dct_drs.keys():
|
||||||
di_supp_node = \
|
# di_supp_node = \
|
||||||
self.firm_prod_network.nodes[di_supp_code]
|
# self.firm_prod_network.nodes[di_supp_code]
|
||||||
di_supp_prod = \
|
# di_supp_prod = \
|
||||||
self.a_lst_total_products.select(
|
# self.a_lst_total_products.select(
|
||||||
[product.code == di_supp_node['Product_Code']
|
# [product.code == di_supp_node['Product_Code']
|
||||||
for product in self.a_lst_total_products])[0]
|
# for product in self.a_lst_total_products])[0]
|
||||||
# find a dfferent firm can produce the same product
|
# # find a dfferent firm can produce the same product
|
||||||
# and is not a current supplier for the same product
|
# # and is not a current supplier for the same product
|
||||||
lst_current_supp_code = \
|
# lst_current_supp_code = \
|
||||||
[self.firm_prod_network.nodes[code]['Firm_Code']
|
# [self.firm_prod_network.nodes[code]['Firm_Code']
|
||||||
for code in self.firm_prod_network.predecessors(
|
# for code in self.firm_prod_network.predecessors(
|
||||||
pro_firm_prod_code)
|
# pro_firm_prod_code)
|
||||||
if self.firm_prod_network.nodes[code][
|
# if self.firm_prod_network.nodes[code][
|
||||||
'Product_Code'] == di_supp_prod.code]
|
# 'Product_Code'] == di_supp_prod.code]
|
||||||
lst_cand = self.model.a_lst_total_firms.select([
|
# lst_cand = self.model.a_lst_total_firms.select([
|
||||||
firm.is_prod_in_current_normal(di_supp_prod)
|
# firm.is_prod_in_current_normal(di_supp_prod)
|
||||||
and firm.code not in lst_current_supp_code
|
# and firm.code not in lst_current_supp_code
|
||||||
for firm in self.model.a_lst_total_firms
|
# for firm in self.model.a_lst_total_firms
|
||||||
])
|
# ])
|
||||||
if len(lst_cand) > 0:
|
# if len(lst_cand) > 0:
|
||||||
select_cand = self.nprandom.choice(lst_cand)
|
# select_cand = self.nprandom.choice(lst_cand)
|
||||||
self.firm_network.graph.add_edges_from([
|
# self.firm_network.graph.add_edges_from([
|
||||||
(self.firm_network.positions[select_cand],
|
# (self.firm_network.positions[select_cand],
|
||||||
self.firm_network.positions[pro_firm], {
|
# self.firm_network.positions[pro_firm], {
|
||||||
'Product': di_supp_prod.code
|
# 'Product': di_supp_prod.code
|
||||||
})
|
# })
|
||||||
])
|
# ])
|
||||||
print(f"proactive add {select_cand.name} to "
|
# # print(f"proactive add {select_cand.name} to "
|
||||||
f"{pro_firm.name} "
|
# # f"{pro_firm.name} "
|
||||||
f"for {di_supp_node['Firm_Code']} "
|
# # f"for {di_supp_node['Firm_Code']} "
|
||||||
f"{di_supp_node['Product_Code']}")
|
# # f"{di_supp_node['Product_Code']}")
|
||||||
# change capacity
|
# # change capacity
|
||||||
select_cand.dct_prod_capacity[di_supp_prod] -= 1
|
# select_cand.dct_prod_capacity[di_supp_prod] -= 1
|
||||||
break
|
# break
|
||||||
# nx.to_pandas_adjacency(G_Firm).to_csv('adj_g_firm_proactive.csv')
|
# # nx.to_pandas_adjacency(G_Firm).to_csv('adj_g_firm_proactive.csv')
|
||||||
|
|
||||||
# draw network
|
# draw network
|
||||||
# self.draw_network()
|
# self.draw_network()
|
||||||
|
@ -349,35 +350,35 @@ class Model(ap.Model):
|
||||||
# reduce the size of disrupted firm
|
# reduce the size of disrupted firm
|
||||||
for firm in self.a_lst_total_firms:
|
for firm in self.a_lst_total_firms:
|
||||||
for prod in firm.dct_prod_up_prod_stat.keys():
|
for prod in firm.dct_prod_up_prod_stat.keys():
|
||||||
status, ts = firm.dct_prod_up_prod_stat[prod]['status'][-1]
|
status, ts = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
|
||||||
if status == 'D':
|
if status == 'D':
|
||||||
size = firm.size_stat[-1][0] - \
|
size = firm.size_stat[-1][0] - \
|
||||||
firm.size_stat[0][0] \
|
firm.size_stat[0][0] \
|
||||||
/ len(firm.dct_prod_up_prod_stat.keys()) \
|
/ len(firm.dct_prod_up_prod_stat.keys()) \
|
||||||
/ self.remove_t
|
/ self.remove_t
|
||||||
firm.size_stat.append((size, self.t))
|
firm.size_stat.append((size, self.t))
|
||||||
print(f'in ts {self.t}, reduce {firm.name} size '
|
# print(f'in ts {self.t}, reduce {firm.name} size '
|
||||||
f'to {firm.size_stat[-1][0]} due to {prod.code}')
|
# f'to {firm.size_stat[-1][0]} due to {prod.code}')
|
||||||
lst_is_disrupt = \
|
lst_is_disrupt = \
|
||||||
[stat == 'D' for stat, _ in
|
[stat == 'D' for stat, _ in
|
||||||
firm.dct_prod_up_prod_stat[prod]['status']
|
firm.dct_prod_up_prod_stat[prod]['p_stat']
|
||||||
[-1 * self.remove_t:]]
|
[-1 * self.remove_t:]]
|
||||||
if all(lst_is_disrupt):
|
if all(lst_is_disrupt):
|
||||||
# turn disrupted firm into removed firm
|
# turn disrupted firm into removed firm
|
||||||
# when last self.remove_t times status is all disrupted
|
# when last self.remove_t times status is all disrupted
|
||||||
firm.dct_prod_up_prod_stat[
|
firm.dct_prod_up_prod_stat[
|
||||||
prod]['status'].append(('R', self.t))
|
prod]['p_stat'].append(('R', self.t))
|
||||||
|
|
||||||
# stop simulation if any firm still in disrupted except inital removal
|
# stop simulation if any firm still in disrupted except initial removal
|
||||||
if self.t > 0:
|
if self.t > 0:
|
||||||
for firm in self.a_lst_total_firms:
|
for firm in self.a_lst_total_firms:
|
||||||
for prod in firm.dct_prod_up_prod_stat.keys():
|
for prod in firm.dct_prod_up_prod_stat.keys():
|
||||||
status, _ = firm.dct_prod_up_prod_stat[prod]['status'][-1]
|
status, _ = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
|
||||||
is_init = \
|
is_init = \
|
||||||
firm in self.dct_lst_init_disrupt_firm_prod.keys() \
|
firm in self.dct_lst_init_disrupt_firm_prod.keys() \
|
||||||
and prod in self.dct_lst_init_disrupt_firm_prod[firm]
|
and prod in self.dct_lst_init_disrupt_firm_prod[firm]
|
||||||
if status == 'D' and not is_init:
|
if status == 'D' and not is_init:
|
||||||
print("not stop because", firm.name, prod.code)
|
# print("not stop because", firm.name, prod.code)
|
||||||
break
|
break
|
||||||
else:
|
else:
|
||||||
continue
|
continue
|
||||||
|
@ -390,19 +391,27 @@ class Model(ap.Model):
|
||||||
self.stop()
|
self.stop()
|
||||||
|
|
||||||
def step(self):
|
def step(self):
|
||||||
print('\n', '=' * 20, 'step', self.t, '=' * 20)
|
# print('\n', '=' * 20, 'step', self.t, '=' * 20)
|
||||||
|
|
||||||
# remove edge to customer and disrupt customer up product
|
# remove edge to customer and disrupt customer up product
|
||||||
for firm in self.a_lst_total_firms:
|
for firm in self.a_lst_total_firms:
|
||||||
for prod in firm.dct_prod_up_prod_stat.keys():
|
for prod in firm.dct_prod_up_prod_stat.keys():
|
||||||
# repetition of disrupted firm that last for multiple ts is ok,
|
# repetition of disrupted firm that last for multiple ts is ok,
|
||||||
# as their edge has already been removed
|
# as their edge has already been removed
|
||||||
status, ts = firm.dct_prod_up_prod_stat[prod]['status'][-1]
|
status, ts = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
|
||||||
if status == 'D' and ts == self.t-1:
|
if status == 'D' and ts == self.t-1:
|
||||||
firm.remove_edge_to_cus_disrupt_cus_up_prod(prod)
|
firm.remove_edge_to_cus(prod)
|
||||||
|
|
||||||
|
for firm in self.a_lst_total_firms:
|
||||||
|
for prod in firm.dct_prod_up_prod_stat.keys():
|
||||||
|
for up_prod in firm.dct_prod_up_prod_stat[prod][
|
||||||
|
's_stat'].keys():
|
||||||
|
if firm.dct_prod_up_prod_stat[prod][
|
||||||
|
's_stat'][up_prod]['set_disrupt_firm']:
|
||||||
|
firm.disrupt_cus_prod(prod, up_prod)
|
||||||
|
|
||||||
for n_trial in range(self.int_n_max_trial):
|
for n_trial in range(self.int_n_max_trial):
|
||||||
print('=' * 10, 'trial', n_trial, '=' * 10)
|
# print('=' * 10, 'trial', n_trial, '=' * 10)
|
||||||
# seek_alt_supply
|
# seek_alt_supply
|
||||||
# shuffle self.a_lst_total_firms
|
# shuffle self.a_lst_total_firms
|
||||||
self.a_lst_total_firms = self.a_lst_total_firms.shuffle()
|
self.a_lst_total_firms = self.a_lst_total_firms.shuffle()
|
||||||
|
@ -410,12 +419,12 @@ class Model(ap.Model):
|
||||||
for firm in self.a_lst_total_firms:
|
for firm in self.a_lst_total_firms:
|
||||||
lst_seek_prod = []
|
lst_seek_prod = []
|
||||||
for prod in firm.dct_prod_up_prod_stat.keys():
|
for prod in firm.dct_prod_up_prod_stat.keys():
|
||||||
status = firm.dct_prod_up_prod_stat[prod]['status'][-1][0]
|
status = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1][0]
|
||||||
if status == 'D':
|
if status == 'D':
|
||||||
for supply in firm.dct_prod_up_prod_stat[
|
for supply in firm.dct_prod_up_prod_stat[
|
||||||
prod]['supply'].keys():
|
prod]['s_stat'].keys():
|
||||||
if not firm.dct_prod_up_prod_stat[
|
if not firm.dct_prod_up_prod_stat[
|
||||||
prod]['supply'][supply]:
|
prod]['s_stat'][supply]['stat']:
|
||||||
lst_seek_prod.append(supply)
|
lst_seek_prod.append(supply)
|
||||||
# commmon supply only seek once
|
# commmon supply only seek once
|
||||||
lst_seek_prod = list(set(lst_seek_prod))
|
lst_seek_prod = list(set(lst_seek_prod))
|
||||||
|
@ -435,11 +444,9 @@ class Model(ap.Model):
|
||||||
|
|
||||||
# reset dct_request_prod_from_firm
|
# reset dct_request_prod_from_firm
|
||||||
self.a_lst_total_firms.clean_before_trial()
|
self.a_lst_total_firms.clean_before_trial()
|
||||||
# do not use:
|
|
||||||
# self.a_lst_total_firms.dct_request_prod_from_firm = {} why?
|
|
||||||
|
|
||||||
def end(self):
|
def end(self):
|
||||||
print('/' * 20, 'output', '/' * 20)
|
# print('/' * 20, 'output', '/' * 20)
|
||||||
|
|
||||||
qry_result = db_session.query(Result).filter_by(s_id=self.sample.id)
|
qry_result = db_session.query(Result).filter_by(s_id=self.sample.id)
|
||||||
if qry_result.count() == 0:
|
if qry_result.count() == 0:
|
||||||
|
@ -448,11 +455,11 @@ class Model(ap.Model):
|
||||||
for prod, dct_status_supply in \
|
for prod, dct_status_supply in \
|
||||||
firm.dct_prod_up_prod_stat.items():
|
firm.dct_prod_up_prod_stat.items():
|
||||||
lst_is_normal = [stat == 'N' for stat, _
|
lst_is_normal = [stat == 'N' for stat, _
|
||||||
in dct_status_supply['status']]
|
in dct_status_supply['p_stat']]
|
||||||
if not all(lst_is_normal):
|
if not all(lst_is_normal):
|
||||||
print(f"{firm.name} {prod.code}:")
|
# print(f"{firm.name} {prod.code}:")
|
||||||
print(dct_status_supply['status'])
|
# print(dct_status_supply['p_stat'])
|
||||||
for status, ts in dct_status_supply['status']:
|
for status, ts in dct_status_supply['p_stat']:
|
||||||
db_r = Result(s_id=self.sample.id,
|
db_r = Result(s_id=self.sample.id,
|
||||||
id_firm=firm.code,
|
id_firm=firm.code,
|
||||||
id_product=prod.code,
|
id_product=prod.code,
|
||||||
|
|
|
@ -1,37 +1,37 @@
|
||||||
X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18,X19,X20,X21,X22,X23
|
X12,X1,X2,X3,X13,X14,X15,X16,X4,X5,X6,X7,X8,X9,X10,X11,X17,X18,X19,X20,X21,X22,X23
|
||||||
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||||
1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1
|
1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1
|
||||||
2,0,0,0,2,2,2,2,2,2,0,0,0,0,0,0,0,0,2,2,2,2,2
|
2,0,0,0,2,2,2,2,0,0,0,0,0,0,0,0,2,2,2,2,2,2,2
|
||||||
0,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,2,2,2,2
|
0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,2,2,2,2
|
||||||
1,0,0,0,1,1,1,2,2,2,0,0,1,1,1,1,1,1,2,0,0,0,0
|
1,0,0,0,1,1,1,2,0,0,1,1,1,1,1,1,2,2,2,0,0,0,0
|
||||||
2,0,0,0,2,2,2,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1
|
2,0,0,0,2,2,2,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1
|
||||||
0,0,0,1,0,1,2,0,1,2,1,1,0,0,0,1,1,1,2,0,1,1,2
|
0,0,0,1,0,1,2,0,1,1,0,0,0,1,1,1,1,2,2,0,1,1,2
|
||||||
1,0,0,1,1,2,0,1,2,0,1,1,0,0,0,1,1,1,0,1,2,2,0
|
1,0,0,1,1,2,0,1,1,1,0,0,0,1,1,1,2,0,0,1,2,2,0
|
||||||
2,0,0,1,2,0,1,2,0,1,1,1,0,0,0,1,1,1,1,2,0,0,1
|
2,0,0,1,2,0,1,2,1,1,0,0,0,1,1,1,0,1,1,2,0,0,1
|
||||||
0,0,1,0,0,2,1,0,2,1,1,1,0,1,1,0,0,1,2,1,0,2,1
|
0,0,1,0,0,2,1,0,1,1,0,1,1,0,0,1,2,1,2,1,0,2,1
|
||||||
1,0,1,0,1,0,2,1,0,2,1,1,0,1,1,0,0,1,0,2,1,0,2
|
1,0,1,0,1,0,2,1,1,1,0,1,1,0,0,1,0,2,0,2,1,0,2
|
||||||
2,0,1,0,2,1,0,2,1,0,1,1,0,1,1,0,0,1,1,0,2,1,0
|
2,0,1,0,2,1,0,2,1,1,0,1,1,0,0,1,1,0,1,0,2,1,0
|
||||||
0,0,1,1,1,2,0,2,1,0,0,1,1,0,1,0,1,0,2,2,1,0,1
|
0,0,1,1,1,2,0,2,0,1,1,0,1,0,1,0,1,0,2,2,1,0,1
|
||||||
1,0,1,1,2,0,1,0,2,1,0,1,1,0,1,0,1,0,0,0,2,1,2
|
1,0,1,1,2,0,1,0,0,1,1,0,1,0,1,0,2,1,0,0,2,1,2
|
||||||
2,0,1,1,0,1,2,1,0,2,0,1,1,0,1,0,1,0,1,1,0,2,0
|
2,0,1,1,0,1,2,1,0,1,1,0,1,0,1,0,0,2,1,1,0,2,0
|
||||||
0,0,1,1,1,2,1,0,0,2,1,0,1,1,0,1,0,0,1,2,2,1,0
|
0,0,1,1,1,2,1,0,1,0,1,1,0,1,0,0,0,2,1,2,2,1,0
|
||||||
1,0,1,1,2,0,2,1,1,0,1,0,1,1,0,1,0,0,2,0,0,2,1
|
1,0,1,1,2,0,2,1,1,0,1,1,0,1,0,0,1,0,2,0,0,2,1
|
||||||
2,0,1,1,0,1,0,2,2,1,1,0,1,1,0,1,0,0,0,1,1,0,2
|
2,0,1,1,0,1,0,2,1,0,1,1,0,1,0,0,2,1,0,1,1,0,2
|
||||||
0,1,0,1,1,0,2,2,2,0,1,0,0,1,1,0,1,0,1,1,0,1,2
|
0,1,0,1,1,0,2,2,1,0,0,1,1,0,1,0,2,0,1,1,0,1,2
|
||||||
1,1,0,1,2,1,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,2,0
|
1,1,0,1,2,1,0,0,1,0,0,1,1,0,1,0,0,1,2,2,1,2,0
|
||||||
2,1,0,1,0,2,1,1,1,2,1,0,0,1,1,0,1,0,0,0,2,0,1
|
2,1,0,1,0,2,1,1,1,0,0,1,1,0,1,0,1,2,0,0,2,0,1
|
||||||
0,1,0,1,1,1,2,2,0,1,0,1,1,1,0,0,0,1,0,0,2,2,1
|
0,1,0,1,1,1,2,2,0,1,1,1,0,0,0,1,0,1,0,0,2,2,1
|
||||||
1,1,0,1,2,2,0,0,1,2,0,1,1,1,0,0,0,1,1,1,0,0,2
|
1,1,0,1,2,2,0,0,0,1,1,1,0,0,0,1,1,2,1,1,0,0,2
|
||||||
2,1,0,1,0,0,1,1,2,0,0,1,1,1,0,0,0,1,2,2,1,1,0
|
2,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,2,0,2,2,1,1,0
|
||||||
0,1,0,0,2,1,0,1,2,2,1,1,1,0,1,1,0,0,0,2,0,1,1
|
0,1,0,0,2,1,0,1,1,1,1,0,1,1,0,0,2,2,0,2,0,1,1
|
||||||
1,1,0,0,0,2,1,2,0,0,1,1,1,0,1,1,0,0,1,0,1,2,2
|
1,1,0,0,0,2,1,2,1,1,1,0,1,1,0,0,0,0,1,0,1,2,2
|
||||||
2,1,0,0,1,0,2,0,1,1,1,1,1,0,1,1,0,0,2,1,2,0,0
|
2,1,0,0,1,0,2,0,1,1,1,0,1,1,0,0,1,1,2,1,2,0,0
|
||||||
0,1,1,1,2,1,1,1,0,0,0,0,0,0,1,1,0,1,2,1,2,0,2
|
0,1,1,1,2,1,1,1,0,0,0,0,1,1,0,1,0,0,2,1,2,0,2
|
||||||
1,1,1,1,0,2,2,2,1,1,0,0,0,0,1,1,0,1,0,2,0,1,0
|
1,1,1,1,0,2,2,2,0,0,0,0,1,1,0,1,1,1,0,2,0,1,0
|
||||||
2,1,1,1,1,0,0,0,2,2,0,0,0,0,1,1,0,1,1,0,1,2,1
|
2,1,1,1,1,0,0,0,0,0,0,0,1,1,0,1,2,2,1,0,1,2,1
|
||||||
0,1,1,0,2,2,2,1,2,1,1,0,1,0,0,0,1,1,1,0,1,0,0
|
0,1,1,0,2,2,2,1,1,0,1,0,0,0,1,1,2,1,1,0,1,0,0
|
||||||
1,1,1,0,0,0,0,2,0,2,1,0,1,0,0,0,1,1,2,1,2,1,1
|
1,1,1,0,0,0,0,2,1,0,1,0,0,0,1,1,0,2,2,1,2,1,1
|
||||||
2,1,1,0,1,1,1,0,1,0,1,0,1,0,0,0,1,1,0,2,0,2,2
|
2,1,1,0,1,1,1,0,1,0,1,0,0,0,1,1,1,0,0,2,0,2,2
|
||||||
0,1,1,0,2,0,1,2,1,2,0,1,0,1,0,1,1,0,0,1,1,2,0
|
0,1,1,0,2,0,1,2,0,1,0,1,0,1,1,0,1,2,0,1,1,2,0
|
||||||
1,1,1,0,0,1,2,0,2,0,0,1,0,1,0,1,1,0,1,2,2,0,1
|
1,1,1,0,0,1,2,0,0,1,0,1,0,1,1,0,2,0,1,2,2,0,1
|
||||||
2,1,1,0,1,2,0,1,0,1,0,1,0,1,0,1,1,0,2,0,0,1,2
|
2,1,1,0,1,2,0,1,0,1,0,1,0,1,1,0,0,1,2,0,0,1,2
|
||||||
|
|
|
BIN
oa_with_exp.xlsx
|
@ -1,2 +1,2 @@
|
||||||
X1,X2,X3,X4,X5,X6,X7,X8,X9,X10
|
X1,X2,X3,X4,X5,X6,X7,X8
|
||||||
0,0,0,0,0,0,0,0,0,0
|
0,0,0,0,0,0,0,0
|
||||||
|
|
|
2
orm.py
|
@ -60,8 +60,6 @@ class Experiment(Base):
|
||||||
cap_limit_prob_type = Column(String(16), nullable=False)
|
cap_limit_prob_type = Column(String(16), nullable=False)
|
||||||
cap_limit_level = Column(DECIMAL(8, 4), nullable=False)
|
cap_limit_level = Column(DECIMAL(8, 4), nullable=False)
|
||||||
diff_new_conn = Column(DECIMAL(8, 4), nullable=False)
|
diff_new_conn = Column(DECIMAL(8, 4), nullable=False)
|
||||||
crit_supplier = Column(DECIMAL(8, 4), nullable=False)
|
|
||||||
proactive_ratio = Column(DECIMAL(8, 4), nullable=False)
|
|
||||||
remove_t = Column(Integer, nullable=False)
|
remove_t = Column(Integer, nullable=False)
|
||||||
netw_prf_n = Column(Integer, nullable=False)
|
netw_prf_n = Column(Integer, nullable=False)
|
||||||
|
|
||||||
|
|
|
@ -9,6 +9,7 @@ class ProductAgent(ap.Agent):
|
||||||
self.name = name
|
self.name = name
|
||||||
|
|
||||||
def a_successors(self):
|
def a_successors(self):
|
||||||
|
# find successors of a product, return in AgentList (ProductAgent)
|
||||||
nodes = self.product_network.graph.successors(
|
nodes = self.product_network.graph.successors(
|
||||||
self.product_network.positions[self])
|
self.product_network.positions[self])
|
||||||
return ap.AgentList(
|
return ap.AgentList(
|
||||||
|
@ -16,6 +17,7 @@ class ProductAgent(ap.Agent):
|
||||||
[ap.AgentIter(self.model, node).to_list()[0] for node in nodes])
|
[ap.AgentIter(self.model, node).to_list()[0] for node in nodes])
|
||||||
|
|
||||||
def a_predecessors(self):
|
def a_predecessors(self):
|
||||||
|
# find predecessors of a product, return in AgentList (ProductAgent)
|
||||||
nodes = self.product_network.graph.predecessors(
|
nodes = self.product_network.graph.predecessors(
|
||||||
self.product_network.positions[self])
|
self.product_network.positions[self])
|
||||||
return ap.AgentList(
|
return ap.AgentList(
|
||||||
|
|
225
test.ipynb
|
@ -1,4 +1,4 @@
|
||||||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,diff_disrupt,proactive_ratio,remove_t,netw_prf_n
|
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n
|
||||||
15,TRUE,TRUE,uniform,5,0.3,2,0.5,0.3,3,3
|
7,TRUE,TRUE,uniform,5,0.3,3,3
|
||||||
10,FALSE,FALSE,normal,10,0.5,1,1,0.5,5,2
|
5,FALSE,FALSE,normal,10,0.5,5,2
|
||||||
5,,,,15,0.7,0.5,2,0.7,7,1
|
3,,,,15,0.7,7,1
|
||||||
|
|
|
|
@ -1,2 +1,2 @@
|
||||||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,proactive_ratio,remove_t,netw_prf_n
|
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n
|
||||||
10,TRUE,TRUE,uniform,10,0.5,0.01,1,5,2
|
5,TRUE,TRUE,uniform,10,0.5,5,2
|
||||||
|
|
|