基于熵-云耦合模型的铁路风吹雪危险度评价

Risk assessment of railway wind andsnow blowing based on entropy-cloudcoupled model

针对我国风吹雪自然灾害突发性、频发性强而传统单因素评价存在不足的现状,尚未有关于铁路风吹雪的危险评价的统一标准,基于熵-云耦合建立铁路风吹雪危险度评价模型,分析了影响铁路风吹雪危险的主要因素,为使各影响因素与评价指标的关系更全面且系统,先综合考虑了自然(外因)和受铁路自身影响(内因)2个方面的因素,共确定出9个主要评价指标;再采用熵权法计算所需评价指标的各个权重,得到了综合确定度,然后结合隶属函数最大原则,对铁路风吹雪危险度进行了评判和预测。同时,结合物元法与熵-云耦合模型的结果进行了对比验证,最后,采用该模型对新疆新建阿-富-准铁路沿线的典型路段进行了危险度判断,结果与实际基本相符。

In view of the sudden and frequent occurrence of wind-blown snow natural disasters in China and the shortcomings of traditional single-factor evaluation,there is no unified standard for the risk evaluation of wind-blown snow on railways.We establish a few sets of systems,like the factor sets,the evaluation sets,and the evaluation weight sets for the risk assessment indexes of snowdrft through the method of entropycloud coupling evaluation.To clarify the relationship between the influential factors and the evaluation indicators,we divide the influential factors into two aspects:the natural factors and the factors influenced by the railway itself with nine safety evaluation indexes.Besides,we also assess the entropy weight method used to calculate the weights of the required evaluation indexes to obtain comprehensive certainty,and then the maximum principle of the membership function is combined.Meanwhile,the results of the matter-element method and entropy-cloud coupling model are compared and verified.Moreover,we combine a vivid description of actual case study samples(the typical section of A-Fu-Zhun railway in A Le Tai,Xinjiang),which involves the investigation and analysis of the actual status in situ.Nevertheless,according to the above application results,the risk probabilities have been identified and determined respectively as grade medium risk,medium risk,high risk,and high risk.Moreover,the risks research sphere involved should be made more comprehensive,and more targeted,to be made in line with the existing conditions.Besides,the results of our evaluation have shown that the Entropy-cloud coupling evaluation model can successfully be used for safety risk assessment of the risk degree of the snowdrift on the railways more reliable and effective.