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Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

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  • Leping He
  • Tao Tang
  • Qijun Hu
  • Qijie Cai
  • Zhijun Li
  • Shaowu Tang
  • Yichun Wang

Abstract

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

Suggested Citation

  • Leping He & Tao Tang & Qijun Hu & Qijie Cai & Zhijun Li & Shaowu Tang & Yichun Wang, 2021. "Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-14, December.
  • Handle: RePEc:hin:jnlmpe:7518284
    DOI: 10.1155/2021/7518284
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    Cited by:

    1. Longlong He & Ruiyu Pan & Yafei Wang & Jiani Gao & Tianze Xu & Naqi Zhang & Yue Wu & Xuhui Zhang, 2024. "A Case Study of Accident Analysis and Prevention for Coal Mining Transportation System Based on FTA-BN-PHA in the Context of Smart Mining Process," Mathematics, MDPI, vol. 12(7), pages 1-31, April.

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