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Research on the Application of Fuzzy Bayesian Network in Risk Assessment of Catenary Construction

Author

Listed:
  • Yongjun Chen

    (School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

  • Xiaojian Li

    (School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

  • Jin Wang

    (School of Civil Engineering, Central South University, Changsha 410075, China
    MOE Key Laboratory of Engineering Structures of Heavy-Haul Railway, Central South University, Changsha 410075, China
    Center for Railway Infrastructure Smart Monitoring and Management, Central South University, Changsha 410075, China)

  • Mei Liu

    (School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

  • Chaoxun Cai

    (State Key Laboratory for Track Technology of High-Speed Railway, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
    Railway Engineering Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China)

  • Yuefeng Shi

    (State Key Laboratory for Track Technology of High-Speed Railway, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
    Railway Engineering Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China)

Abstract

The research on risk control during the construction stage of catenary is relatively limited. Based on a comprehensive analysis of the risk factors during catenary construction, this study determined the causal relationships between the risk factors and established a risk assessment model for catenary construction that analyzed the risks from a causal logic perspective. During the evaluation process, we identified six exogenous variables and twenty-one endogenous variables for risk factors in the construction of catenary based on a literature review in the field of catenary construction and expert opinions, described the cause-and-effect relationships between variables using structural equations and causal diagrams, and established a multi-level catenary construction risks structural causal model. Based on expert fuzzy evaluation and expert experience, the occurrence probability of exogenous variables and the conditional probability of endogenous variables were determined, respectively. Then, the risk assessment model of catenary construction stage based on fuzzy Bayesian Network was constructed to analyze the risk of catenary construction process. The results showed that the personal quality of the construction personnel and the sense of responsibility of the supervision unit had a great impact on the risk level of catenary construction. The findings can help construction personnel fully consider various weak points in catenary construction, thereby ensuring efficient and high-quality catenary construction.

Suggested Citation

  • Yongjun Chen & Xiaojian Li & Jin Wang & Mei Liu & Chaoxun Cai & Yuefeng Shi, 2023. "Research on the Application of Fuzzy Bayesian Network in Risk Assessment of Catenary Construction," Mathematics, MDPI, vol. 11(7), pages 1-19, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1719-:d:1115265
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    References listed on IDEAS

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    4. Sang-Guk Yum & Kiyoung Son & Seunghyun Son & Ji-Myong Kim, 2020. "Identifying Risk Indicators for Natural Hazard-Related Power Outages as a Component of Risk Assessment: An Analysis Using Power Outage Data from Hurricane Irma," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
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    Cited by:

    1. Rui Han & Shiqi Yang, 2023. "A Study on Industrial Heritage Renewal Strategy Based on Hybrid Bayesian Network," Sustainability, MDPI, vol. 15(13), pages 1-32, July.

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