交通运输研究2024，Vol.10Issue(1)：36-44,9.DOI:10.16503/j.cnki.2095-9931.2024.01.005
基于ELM神经网络的高速公路隧道运营风险评估模型
An Operation Risk Assessment Model for Highway Tunnels Based on ELM Neural Network
摘要
Abstract
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.关键词
交通工程/隧道运营安全/极限学习机/风险评估/风险管控Key words
traffic engineering/operation safety of tunnels/ELM(Extreme Learning Machine)/risk assessment/risk management and control分类
交通工程引用本文复制引用
李然,朱本成,郭云鹏,李凯伦..基于ELM神经网络的高速公路隧道运营风险评估模型[J].交通运输研究,2024,10(1):36-44,9.基金项目
中央级公益性科研院所基本科研业务费项目(20210502 （）
20230501) （）
