Volume 42 Issue 3
Jun.  2024
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Article Contents
WU Xiumei, SHI Zhan, YUAN Xiang, CAI Wenjuan. An Evaluation Method of Safety Resilience for Highway Bridge Engineering Based on an Entropy Weight and Improved TOPSIS Model[J]. Journal of Transport Information and Safety, 2024, 42(3): 139-147. doi: 10.3963/j.jssn.1674-4861.2024.03.015
Citation: WU Xiumei, SHI Zhan, YUAN Xiang, CAI Wenjuan. An Evaluation Method of Safety Resilience for Highway Bridge Engineering Based on an Entropy Weight and Improved TOPSIS Model[J]. Journal of Transport Information and Safety, 2024, 42(3): 139-147. doi: 10.3963/j.jssn.1674-4861.2024.03.015

An Evaluation Method of Safety Resilience for Highway Bridge Engineering Based on an Entropy Weight and Improved TOPSIS Model

doi: 10.3963/j.jssn.1674-4861.2024.03.015
  • Received Date: 2023-12-28
    Available Online: 2024-10-21
  • Targeting to the safety risks in freeway bridge construction caused by inadequate safety management, this paper develops a safety resilience evaluation method for bridge construction considering the full lifecycle of risk-hazard-accident. Based on bibliometric analysis and WBS theory, the concept of resilience is integrated into safety evaluation for traffic engineering. An evaluation system for freeway bridge engineering based on safety resilience theory is proposed, where the safety resilience mechanism of freeway bridge construction is investigated and evaluation index system with"4R"characteristics as primary indicators are developed. Given that traditional technique for order preference by similarity to an ideal solution (TOPSIS) evaluation does not account for the impact of outliers, statistical methods are used to screen and resample the outliers. Meanwhile, entropy weight method is adopted to optimize the weights of indices. By doing so, an entropy weight-improved TOPSIS model is developed for safety resilience evaluation of bridge engineering. Four freeway sections containing bridge construction are selected and their levels of safety resilience are evaluated using the proposed model, whose feasibility is analyzed as well. Results show Sections B and D have a medium level of safety resilience, while Sections A and C have a low level. Comparing to the results from the traditional risk assessment method that Sections B and D are Level Ⅰ and Sections A and C are Level Ⅱ, results from the proposed model align with real situations. Therefore, the validity and feasibility of the model are confirmed. To sum up, the proposed entropy weight-improved TOPSIS model enables sensitivity analysis and risk factor tracing, and further contributes to targeted preemptive improvements for decision-makers.

     

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