Yong Qin, Zhenyu Zhang, Bo Chen, Z. Xing, Jing Liu, Jun Li
{"title":"Research on the Prediction Model for the Security Situation of Metro Station Based on PSO/SVM","authors":"Yong Qin, Zhenyu Zhang, Bo Chen, Z. Xing, Jing Liu, Jun Li","doi":"10.4236/JILSA.2013.54028","DOIUrl":null,"url":null,"abstract":"Security situation awareness is a new \ntechnology about security. This paper brings it to the assessment of security \nsituation of metro station which serves as a new way to secure the security of \npassengers as well as the operation of the metro station. This paper sets up an \nindex system for assessing the security situation awareness and makes a \nprediction model for the security situation of metro station based on PSO/SVM \nafter doing lots of researches and analyses. Furthermore, through case studies, we find that the \nmodel has high accuracy and ability to accurately predict the security \nsituation of metro station in the future and a certain practical value.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"智能学习系统与应用(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.4236/JILSA.2013.54028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Security situation awareness is a new
technology about security. This paper brings it to the assessment of security
situation of metro station which serves as a new way to secure the security of
passengers as well as the operation of the metro station. This paper sets up an
index system for assessing the security situation awareness and makes a
prediction model for the security situation of metro station based on PSO/SVM
after doing lots of researches and analyses. Furthermore, through case studies, we find that the
model has high accuracy and ability to accurately predict the security
situation of metro station in the future and a certain practical value.