title: High speed railway environment safety evaluation based on measurement attribute recognition model.
abstract: In order to rationally evaluate the high speed railway operation safety level, the environmental safety evaluation index system of high speed railway should be well established by means of analyzing the impact mechanism of severe weather such as raining, thundering, lightning, earthquake, winding, and snowing. In addition to that, the attribute recognition will be identified to determine the similarity between samples and their corresponding attribute classes on the multidimensional space, which is on the basis of the Mahalanobis distance measurement function in terms of Mahalanobis distance with the characteristics of noncorrelation and nondimensionless influence. On top of the assumption, the high speed railway of China environment safety situation will be well elaborated by the suggested methods. The results from the detailed analysis show that the evaluation is basically matched up with the actual situation and could lay a scientific foundation for the high speed railway operation safety.
authors.affiliation: School of Automation, Nanjing University of Science & Technology, Nanjing, Jiangsu 2100984, China.
authors.forename: Qizhou
authors.initials: Q
authors.lastname: Hu
authors.affiliation: School of Automation, Nanjing University of Science & Technology, Nanjing, Jiangsu 2100984, China.
authors.forename: Ningbo
authors.identifier: 0000-0003-1777-8217
authors.initials: N
authors.lastname: Gao
authors.affiliation: East China Jiaotong University, Nanchang, Jiangxi 330013, China.
authors.forename: Bing
authors.initials: B
authors.lastname: Zhang
mesh_terms: D002681:China; D004777:Environment; D004784:Environmental Monitoring; D006801:Humans; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D011890:Railroads; D012449:Safety