摘要
铁路建设风险评估是铁路建设项目中重要的一环。针对传统铁路建设风险评估方法中存在的不足,本文提出了一种基于粒子群优化的交互变量BP神经网络评估模型,并将其应用于欧洲国家铁路建设的风险评估,训练集评估结果和验证集评估结果均显示该模型能够有效地预测评估铁路建设的风险等级,具有较高的评估精度。
Risk assessment of railway construction is an important part of railway construction project.In view of shortcomings in traditional risk assessment methods for railway construction,this paper builds an interactive variable BP(Back Propagation)neural network model based on particle swarm optimization and applies it to the risk assessment of railway construction in European countries.The evaluation results of the training set and the verification set all show that this model can effectively predict and evaluate the risk level of railway construction and has a high evaluation accuracy.
作者
吴志强
王波
WU Zhiqiang;WANG Bo(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《软件工程》
2020年第10期26-29,共4页
Software Engineering
关键词
铁路建设
风险评估
BP神经网络
交互变量
粒子群算法
railway construction
risk assessment
BP neural network
interaction variables
particle swarm optimization algorithm
