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Computational Intelligence and Neuroscience
Volume 2014, Article ID 470758, 10 pages
http://dx.doi.org/10.1155/2014/470758
Research Article

High Speed Railway Environment Safety Evaluation Based on Measurement Attribute Recognition Model

1School of Automation, Nanjing University of Science & Technology, Nanjing, Jiangsu 2100984, China
2East China Jiaotong University, Nanchang, Jiangxi 330013, China

Received 20 July 2014; Revised 22 September 2014; Accepted 25 September 2014; Published 9 November 2014

Academic Editor: Yongjun Shen

Copyright © 2014 Qizhou Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.