A data-driven approach to anomaly detection and vulnerability dynamic analysis for large-scale integrated energy systems
Li ZhangNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, ChinaHuai SuNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, ChinaEnrico ZioDepartment of Nuclear Engineering, College of Engineering, Kyung Hee University, Republic of KoreaZhien ZhangWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USALixun ChiNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, ChinaLin FanNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, ChinaJing ZhouNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, ChinaJinjun ZhangNational Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249 Beijing, China
2021en
ABI
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Cited by 20 references