Metro Station Safety Status Prediction Based on GA-SVR

被引：4

作者：

Zhang, Zhenyu ^{[1
]}

Qin, Yong ^{[1
]}

Cheng, Xiaoqing ^{[1
]}

Zhu, Lei ^{[1
]}

Kou, Linlin ^{[1
]}

Li, Jian ^{[2
]}

Sun, Fang ^{[2
]}

机构：

[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China

[2] Beijing Traff Control Ctr, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION: TRANSPORTATION | 2016年 / 378卷

关键词：

Metro station; Safety status prediction; Genetic algorithm; Support vector regression;

D O I：

10.1007/978-3-662-49370-0_7

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Metro station is one of the most important parts in the metro system. Once an accident occurs, it will cause a lot of casualties and property losses. To ensure the safety of the station operation, accurately predicting the safety status of metro station is of great significance. The paper analyzed the influencing factors of metro station's safety status, and established the metro station safety status prediction model based on GA-SVR. The results show that safety status prediction model based on GA-SVR can predict the trend of metro station safety status accurately, which makes the change from passive safety to active safety and has good practical value.

引用

页码：57 / 69

页数：13

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