基于粗糙集条件信息熵的山岭隧道坍塌风险评价

Risk assessment of mountain tunnel collapse based on rough set and conditional information entropy

坍塌是山岭隧道施工过程中主要灾害之一。由于影响坍塌的因素众多,且各因素所占的权重差异较大,甚至有些因素是不必要或冗余的。目前常用的评价方法不但未对这些不必要或冗余的因素进行筛选,而且权重的确定过于依赖专家经验和主观赋值,导致风险评价结果精度低、可靠性差。基于此,应用粗糙集理论在数据挖掘、指标筛选和重要性计算方面的优势,将山岭隧道坍塌风险评价构建为粗糙集的决策信息表。但工程试验发现,基于传统依赖度的属性约简及权重计算不能满足要求,存在计算权重为0或约简结果过多,无法取舍的问题。针对以上问题,提出了一种基于条件信息熵的计算方法,该方法将条件信息熵引入到属性重要度和权重的定义中,同时以最重要的条件属性为起点,逐步增添属性,实现属性约简。所建立的方法既能从大量影响因素中,提取出主要影响因素,剔除相对冗余或不重要的因素;同时又能计算得到各因素的客观权重。最后结合模糊综合评价法,建立了基于粗糙集条件信息熵的山岭隧道坍塌风险评价模型,并成功应用于秀村隧道中,表明该模型可靠、实用,为山岭隧道坍塌风险评价提供一条新的研究思路。

Collapse is one of the major disasters in the construction of mountain tunnels. Because there are many factors affecting the collapse, and the weight of each factor varies greatly, even some factors are unnecessary or redundant. At present, the commonly used evaluation methods not only fail to screen these unnecessary or redundant factors, but also rely too much on expert experience and subjective evaluation to determine the weight, resulting in low accuracy and poor reliability of risk assessment results. Based on this, considering the advantage of rough set theory in data mining, index screening and importance computation, the risk assessment of mountain tunnel collapse is constructed as the decision information table of rough set. However, in the engineering experiment, it is found that the attribute reduction and weight calculation based on the traditional dependency degree can not meet the requirements, and there is a problem that the weight of calculation is zero or the reduction result is too much and can not be taken out. In view of the above problems, a method based on conditional information entropy is proposed, which introduces conditional information entropy into the definition of attribute importance and weight. At the same time, the most important conditional attributes are taken as the starting point, and attributes are gradually added to realize attribute reduction. The method established in this paper can not only extract the main influencing factors from a large number of influencing factors, but also eliminate the relatively redundant or unimportant factors. At the same time, it can calculate the objective weight of each factor. Then combined with fuzzy comprehensive evaluation method, the risk evaluation model of mountain tunnel collapse based on rough set and conditional information entropy is established and successfully applied to the Xiucun tunnel. It shows that the model is reliable and practical, and provides a new research idea for the risk assessment of mountain tunnel collapse.