Research on High-Speed Railway Safety Management Based on Global Data Management

Chang Liu (), Dan Chang () and Daqing Gong ()
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Chang Liu: Beijing Jiaotong University
Dan Chang: Beijing Jiaotong University
Daqing Gong: Beijing Jiaotong University

A chapter in IEIS 2023, 2024, pp 156-166 from Springer

Abstract: Abstract High-speed railway data assets provide basic support for analyzing railway safety management and discovering accident rules. Based on the analysis of the current data management situation in China’s railway industry, combined with the characteristics of a complex network and large linkage of railway global data, this paper studies the integration theoretical model of railway global risk prevention and control. It analyzes the big data requirements of railway global data management from three aspects of the “human-machine-environment” and finally realizes the real-time accuracy of railway global risk prevention and control. To minimize the overall operation risk, improve the intelligent level of railway safety prevention and control.

Keywords: Global data management; Big data demand; Safety management (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-97-4137-3_13

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DOI: 10.1007/978-981-97-4137-3_13

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