基于主成分分析法的危险货物运输企业安全评价

为更准确地评估危险货物运输企业安全等级以降低其运输风险,提出基于主成分分析法(PCA)的危险货物运输企业BP神经网络安全评价模型;在从人-机-物-环境-管理角度构建危险货物运输企业安全评价指标的基础上,分别利用该模型和其他3种模型对3家实例企业进行仿真评价和对比分析。结果表明,该模型的评价结果与期望值间的相对误差约为0.5%～1.2%,计算精度优于其他模型,且具有计算量小等特点。

A Safety Assessment Model for Hazardous Material Transportation Enterprises Based on Principle Component Analysis

For more accurately assessing the safety level of hazardous materials(hazmat) transportation enterprises to reduce their transportation risk,a safety assessment model on the basis of the PCA and BP neural network was proposed.Based on the determined safety assessment index system for hazmat transport enterprises in terms of people-vehicle-material-environment-management,three enterprises were taken as examples for simulation evaluation and comparative analysis by using this model and three others respectively.The results show that the relative error between evaluating value and expectation is 0.5%-1.2%,its calculation accuracy is higher than that of others,with a good characteristic of small calculation.