基于模糊证据推理的铁路隧道施工风险评估模型建构

研究基于模糊证据推理的铁路隧道施工风险评估模型,是一个模糊神经网络配合加权指标模型。其模糊神经网络的数据模糊使用数据投影法、归一化法、去量纲法等前置模糊算法,形成14个Double格式数据并输入到多列神经网络后,使用4个相对独立的解模糊模块对数据进行解析,形成针对4个特定事故风险的评价结果。使用加权指标法对4个指标进行整合,形成总体评价指标。通过真实数据的仿真分析,对比技术领域常用的2套成型软件,在评价敏感性不变的前提下,其评价特异性从10%提升至95%以上。

Construction of Railway Tunnel Construction Risk Assessment Model Based on Fuzzy Evidence Reasoning

Research on the risk assessment model of railway tunnel construction based on fuzzy evidence reasoning,which is a fuzzy neural network with weighted index model.The data fuzzing of the fuzzy neural network uses the data projection method,the normalization method,the de-dimensional method&other pre-fuzzy algorithms to form 14 Double format data and input them into the multi-column neural network;to use 4 relatively independent defuzzification module to analyze the data,and to form the evaluation results for 4 specific accident risks.Use the weighted index method to integrate the 4 indexes to form an overall evaluation index.The weighted index method is used to integrate the 4 indexes to form the overall evaluation index.Through the simulation analysis of real data,compared with the 2 sets of molding software commonly used in the technical field,the evaluation specificity is improved from 10%to more than 95%on the premise of the same evaluation sensitivity.