An Operation Risk Assessment Model for Highway Tunnels Based on ELM Neural Network
To overcome the problems of traditional operation risk assessment methods of highway tunnels,such as cumbersome calculation process,low computational efficiency and poor generalization ability,this paper conducted an operation risk assessment model of highway tunnels based on the ELM(Extreme Learning Machine)neural network.Firstly,based on the theory of systems engineering,the factors affect-ing operation risk of highway tunnels were analyzed,and the evaluation index system of operation risk was constructed.Then,taking the actual operation accident data of 126 tunnels in China as the sample set,the Sigmoid function was determined as the activation function based on comparing the classification ac-curacy rate and test time of different function.An operation risk assessment model of highway tunnels based on ELM neural network algorithm was trained.Finally,using this model as the core algorithm,an operation risk assessment system of highway tunnels was developed and applied to a highway in Guangdong Province,China.The results showed that the proposed risk assessment model simplified the manual calculation process and could improve the timeliness and effectiveness of operation risk assessment of highway tunnel.
traffic engineeringoperation safety of tunnelsELM(Extreme Learning Machine)risk assessmentrisk management and control
国家科技期刊平台
NSTL
万方数据
维普
