Fuzzy-Bayesian-network-based Safety Risk Analysis in Railway Passenger Transport

Authors

  • Dongye Sun
    Affiliation
    MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology, School of Traffic and Transportation, Beijing Jiaotong University, China
  • Yuanhua Jia
    Affiliation
    MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology, School of Traffic and Transportation, Beijing Jiaotong University, China
  • Yang Yang
    Affiliation
    MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology, School of Traffic and Transportation, Beijing Jiaotong University, China
  • Huanan Li
    Affiliation
    MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology, School of Traffic and Transportation, Beijing Jiaotong University, China
  • Liping Zhao
    Affiliation
    School of Economics and Management, Beijing Jiaotong University, China
https://doi.org/10.3311/PPtr.11489

Abstract

This study presents a fuzzy Bayesian network (FBN) method to analyze the influence on the safety risk of railway passenger transport applying different risk control strategies. Based on the fuzzy probability of the basic event determined by the expert group decision method, the proposed FBN method can reasonably predict the probability of railway passenger safety risk. It is also proven that control the risk in the safety management of railway passenger transport will be the most effective way to reduce the risk probability of the railway passenger transport safety.

Keywords:

railway passenger transport, fuzzy Bayesian network, probabilistic forecast modeling, safety risk analysis, fuzzy probability reasoning

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Published Online

2018-01-10

How to Cite

Sun, D., Jia, Y., Yang, Y., Li, H., Zhao, L. (2018) “Fuzzy-Bayesian-network-based Safety Risk Analysis in Railway Passenger Transport”, Periodica Polytechnica Transportation Engineering, 46(3), pp. 135–141. https://doi.org/10.3311/PPtr.11489

Issue

Vol. 46 No. 3 (2018)

Section

Articles