Natural disaster warning system for safe operation of a high-speed railway. Issue 4 (23rd September 2021)

• Record Type: Journal Article
• Authors: Qizhou, Hu; Xin, Fang; Lishuang, Bian
• Is Part Of: Transportation safety and environment. Volume 3:Issue 4(2021)
• Publication Date: 2021-09-23
• Subjects: high-speed railway -- safe operation -- natural disaster early warning system -- least square support vector machine (LSSVM); Transportation engineering -- Periodicals; Transportation -- Safety measures -- Periodicals; 629.04
• DOI: 10.1093/tse/tdab019
• Languages: English
• ISSNs: 2631-4428

Abstract

Abstract: In this paper, the least square support vector machine (LSSVM) is used to study the safety of a high-speed railway. According to the principle of LSSVM regression prediction, the parameters of the LSSVM are optimized to model the natural disaster early warning of safe operation of a high-speed railway, and the management measures and methods of high-speed railway safety operation under natural disasters are given. The relevant statistical data of China's high-speed railway are used for training and verification. The experimental results show that the LSSVM can well reflect the nonlinear relationship between the accident rate and the influencing factors, with high simulation accuracy and strong generalization ability, and can effectively predict the natural disasters in the safe operation of a high-speed railway. Moreover, the early warning system can improve the ability of safety operation evaluation and early warning of high-speed railway under natural disasters, realize the development goals of high-speed railway (safety, speed, economic, low-carbon and environmental protection) and provide a theoretical basis and technical support for improving the safety of a high-speed railway.