Data-driven accident consequence assessment on urban gas pipeline network based on machine learning

被引：0
|
作者：
Yang, Yang [1 ,2 ]
Li, Suzhen [1 ]
Zhang, Pengcheng [3 ]
机构：
[1] College of Civil Engineering, Tongji University, Shanghai,200092, China
[2] Department of Civil and Environmental Engineering, University of California, Berkeley,CA,94720, United States
[3] Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou,510060, China
来源：
Reliability Engineering and System Safety | 2022年 / 219卷
基金：
中国国家自然科学基金;
关键词：
Information management - Pipelines - Accidents - Risk assessment - Anomaly detection - Losses - Topology - Clustering algorithms - Convolution - Machine learning;
D O I：
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中图分类号：
学科分类号：
摘要：
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