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With the rapid growth of cities worldwide, the demand for tunneling projects has surged, characterized by their large scale and significant uncertainty. As project scale and complexity increase, risk control becomes crucial for ensuring underground construction safety (Zhang et al. in Knowl-Based Syst 132:30–46, 2017 [1]). However, while complex projects generate vast amounts of information, the risk assessment often relies on static data (missing the dynamic nature), and current risk management practices are still largely manual and depend on experience and mathematical analysis. Therefore, enhancing existing risk management practices with a system that can perceive risk probabilities in real time is an urgent and valuable step forward (Guo and Zhang in Knowl-Based Syst 227, 2021 [2]).

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Safety Risk Assessment

  • 章节

  • 发表日期：

    2025年

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  • Limao Zhang,
  • Yue Pan,
  • Penghui Lin,
  • Mirosław J. Skibniewski

摘要

With the rapid growth of cities worldwide, the demand for tunneling projects has surged, characterized by their large scale and significant uncertainty. As project scale and complexity increase, risk control becomes crucial for ensuring underground construction safety (Zhang et al. in Knowl-Based Syst 132:30–46, 2017 [1]). However, while complex projects generate vast amounts of information, the risk assessment often relies on static data (missing the dynamic nature), and current risk management practices are still largely manual and depend on experience and mathematical analysis. Therefore, enhancing existing risk management practices with a system that can perceive risk probabilities in real time is an urgent and valuable step forward (Guo and Zhang in Knowl-Based Syst 227, 2021 [2]).