为更准确、更科学地完成山岭隧道塌方风险评价，提出一种基于层次分析法（AHP）-熵值法（Entropy）集对分析理论的山岭隧道塌方风险评价方法。首先，选取地质因素、设计因素、施工因素、管理因素4项因素作为塌方风险评价指标体系的准则层，选取12项因素作为指标层，运用层次分析法和熵值法分别计算2级指标权重；然后，引入集对分析理论确定指标联系度，并结合置信度准则对塌方风险的等级进行判定；接着，利用Grasshopper以及Python软件，对集对分析理论进行可视化程序开发，并将其与隧道-地质BIM交互模型进行耦合，建立基于AHP-Entropy集对分析模型的隧道塌方风险数字化分析平台；最后，结合重庆某隧道实际工程，验证隧道塌方风险评价的高效化、可视化效果。研究表明：
基于集对分析理论的山岭隧道塌方风险评价数字化分析平台运行时间约为2 s，与传统的隧道塌方风险评价方法相比可以大大提高风险评价效率，同时利用AHP-Entropy法确定评价指标权重，提高了评价结果的可靠性。
A risk assessment method for mountain tunnel collapse
based on analytic hierarchy process(AHP)entropy method and setpair analysis(SPA) theory is proposed to enhance the accuracy and
scientific validity of evaluations. Initially, a risk assessment system
comprising 12 factors is constructed. Subsequent steps involve the utilization
of AHP and entropy methods to calculate the weights of two levels of indices.
SPA is then applied to ascertain the correlation degree among indices, with the
collapse risk level determined using a confidence criterion. Furthermore, a
visual programming application based on SPA theory is developed using
Grasshopper and Python software, and integrated with a tunnelgeological building information modeling interaction model. Finally,
a digital evaluation platform for tunnel collapse risk based on the AHPentropy set analysis model is established. This platform facilitates
efficient, visualized, and scientific assessment of tunnel collapse risk. The
efficacy of this platform has been validated through its application in a
tunnel project in Chongqing, demonstrating that the SPA theorybased digital platform for mountain tunnel collapse risk assessment
operates only for 2 s. This considerably enhances the efficiency of risk
assessment, while the evaluation index weight determined using the AHPentropy method considerably improves the reliability of the
evaluation outcomes.
