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1. 发明申请

US20170015339A1 COMPLEX NETWORK-BASED HIGH SPEED TRAIN SYSTEM SAFETY EVALUATION METHOD 有权
标题翻译：基于复杂网络的高速火车系统安全评估方法
公开(公告)号：US20170015339A1
公开(公告)日：2017-01-19
申请号：US15123684
申请日：2015-11-27
申请人： BEIJING JIAOTONG UNIVERSITY
发明人： Limin JIA , Yong QIN , Yanhui WANG , Shuai LIN , Hao SHI , Lifeng BI , Lei GUO , Lijie LI , Man LI
IPC分类号： B61L99/00 , G06N99/00 , H04L29/08
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.
摘要翻译：本发明公开了一种基于复杂网络的高速列车系统安全评估方法。该方法包括以下步骤：（1）构建高速列车系统物理结构的网络模型，并根据网络模型构建节点的功能属性度; （2）提取组件故障之间的功能属性度，故障率和平均时间作为输入量，使用LIBSVM软件进行SVM训练; （3）进行加权kNN-SVM判断：判断为不可分类的采样点，以获得高速列车系统的安全等级。对于具有复杂的物理结构和操作条件的高速列车系统，当系统中的部件的状态改变时，该方法可以评估对系统安全性的影响程度。实验结果表明该算法精度高，实用性好。

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