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公开(公告)号:US09630637B2
公开(公告)日:2017-04-25
申请号:US15123684
申请日:2015-11-27
发明人: Limin Jia , Yong Qin , Yanhui Wang , Shuai Lin , Hao Shi , Lifeng Bi , Lei Guo , Lijie Li , Man Li
CPC分类号: B61L99/00 , B61L27/0055 , B61L27/0083 , G06F17/50 , G06N99/005 , H04L67/12
摘要: The invention discloses a complex network-based high speed train system safety evaluation method. The method includes steps as follows: (1) constructing a network model of a physical structure of a high speed train system, and constructing a functional attribute degree of a node based on the network model; (2) extracting a functional attribute degree, a failure rate and mean time between failures of a component as an input quantity, conducting an SVM training using LIBSVM software; (3) conducting a weighted kNN-SVM judgment: an unclassifiable sample point is judged so as to obtain a safety level of the high speed train system. For a high speed train system having a complicated physical structure and operation conditions, the method can evaluate the degree of influences on system safety when a state of a component in the system changes. The experimental result shows that the algorithm has high accuracy and good practicality.