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HaoYizhi b17dec4dbe experiments'
2023-07-03 12:42:20 +08:00
__pycache__
experiments'
2023-07-03 12:42:20 +08:00
.vscode
experiments'
2023-07-03 12:40:10 +08:00
analysis
before proactive
2023-06-04 18:43:49 +08:00
adj_g_firm_proactive.csv
graph inconsistant
2023-06-10 23:48:11 +08:00
adj_g_firm_prod.csv
graph inconsistant
2023-06-10 23:48:11 +08:00
adj_g_firm.csv
graph inconsistant
2023-06-10 23:48:11 +08:00
AmendFirm_20230216.ipynb
analysis
2023-05-15 10:42:16 +08:00
analysis_count.py
analysis
2023-05-15 10:42:16 +08:00
analysis_firm_network.py
before proactive
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analysis_prod_network.py
analysis
2023-05-15 10:42:16 +08:00
analysis_prod.py
analysis
2023-05-15 10:42:16 +08:00
anova.py
proactive strategy anova
2023-06-05 16:06:18 +08:00
anova.xlsx
before proactive
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BomCateNet_Supply.csv
1st commit
2023-02-12 21:44:08 +08:00
BomCateNet.csv
AmendFirm
2023-02-16 16:11:54 +08:00
BomNodes.csv
1st commit
2023-02-12 21:44:08 +08:00
computation.py
format
2023-05-15 13:45:07 +08:00
conf_db_prefix.yaml
experiments'
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conf_db.yaml
data collection
2023-03-12 12:02:01 +08:00
conf_experiment.yaml
set maximun interation limit: para n_iter
2023-07-02 15:17:58 +08:00
controller_db.py
experiments'
2023-07-03 12:42:20 +08:00
Firm_amended_count_product.csv
model product firm
2023-03-06 22:38:57 +08:00
Firm_amended.csv
Amend Firm Finished!
2023-02-20 20:56:27 +08:00
Firm_ori.csv
Firm.csv
2023-02-13 17:52:58 +08:00
Firm.csv
Amend Firm Finished!
2023-02-20 20:56:27 +08:00
firm.py
baseline
2023-07-02 23:34:44 +08:00
Firm.xlsx
Amend Firm Finished!
2023-02-20 20:56:27 +08:00
InitRemovalHighRisk.csv
with_exp
2023-05-21 17:05:06 +08:00
LoadFirm_20230213-1.ipynb
Load Firm - choose customer
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LoadFirm_20230213-1.png
Amend firm based on size
2023-02-20 16:02:39 +08:00
LoadNetworkx_20230210-1.ipynb
model firm
2023-02-25 20:14:53 +08:00
LoadNetworkx_20230210-1.png
Amend firm based on size
2023-02-20 17:03:36 +08:00
LoadNetworkx_20230210-1.py
requirement.txt
2023-02-12 22:19:13 +08:00
main.py
remove firm that denied request from candidate list
2023-05-15 13:37:05 +08:00
MarketWatch.csv
Firm Addition
2023-02-18 16:46:38 +08:00
MarketWatch.ipynb
Firm Addition
2023-02-18 16:46:38 +08:00
model.py
baseline
2023-07-02 23:34:44 +08:00
myfile.json
handling request based on connection
2023-03-16 16:08:45 +08:00
network1.png
database store graph
2023-03-16 15:07:43 +08:00
network.png
generate network pred + succ
2023-06-11 13:17:34 +08:00
oa_L27.txt
with_exp
2023-05-21 17:05:06 +08:00
oa_L36.txt
with exp
2023-06-11 22:42:04 +08:00
oa_with_exp.csv
no need for resetting random generator with seed
2023-06-16 17:15:17 +08:00
oa_with_exp.xlsx
experiments'
2023-07-03 12:40:10 +08:00
oa_without_exp.csv
remove disrupt to removed, 3 status (Normal / Affected / Removed) + size_stat
2023-07-02 13:00:13 +08:00
orm.py
log status of every firm product in every time step + mysql
2023-07-02 20:44:06 +08:00
product.py
remove firm that denied request from candidate list
2023-05-15 13:37:05 +08:00
pygraphviz-1.9-cp38-cp38-win_amd64.whl
change system
2023-03-04 17:49:13 +08:00
requirements_manual_selected_20230304.txt
change system
2023-03-04 17:49:13 +08:00
requirements.txt
data collection
2023-03-12 12:02:01 +08:00
size_stats.py
analysis
2023-05-15 10:42:16 +08:00
SQL_check_num_dis_firm_in_ts.sql
with exp
2023-06-11 22:42:04 +08:00
SQL_export_high_risk_setting.sql
experiments'
2023-07-03 12:40:10 +08:00
SQL_find_high_risk_setting.sql
experiments'
2023-07-03 12:40:10 +08:00
SQL_migrate_db.sql
with_exp
2023-05-21 17:05:06 +08:00
SQL_running_check.sql
no need for resetting random generator with seed
2023-06-16 17:15:17 +08:00
sum_result.py
before proactive
2023-06-04 18:43:49 +08:00
test.ipynb
experiments'
2023-07-03 12:40:10 +08:00
test.py
database store graph
2023-03-16 15:07:43 +08:00
xv_with_exp.csv
baseline
2023-07-02 23:30:42 +08:00
xv_without_exp.csv
baseline
2023-07-02 23:30:42 +08:00
全部A股(1).xlsx
Firm addition
2023-02-16 18:53:40 +08:00
批量查询_ifind企业库示例文件.xlsx
Firm Addition
2023-02-17 12:03:47 +08:00
Description
Agent-based model for industrial Internet
167 MiB
Languages
Jupyter Notebook 99.2%
Python 0.8%