交通信息与安全2013，Vol.31Issue(2)：104-108,5.DOI:10.3963/j.issn1674-4861.2013.02.023
基于神经网络的公路边坡稳定性实时判断
Real-time Stability Analysis of Roadside Bank Based on Modular Neural Network
摘要
Abstract
In order to provide early warning to roadside bank stability problem, This paper builds a mathematical model between safety factors of roadside bank stability Fs and deformation value based on artificial neural network (ANN). It can work out Fs with real-time deformation value to roadside bank, thus overcoming the weakness that Fs can 't be obtained in time. Using this method, real-time warning of cohesionless (non-clay) soil-based roadside bank stability problem can be provided by using Fs. In comparison, for the same purpose the traditional real-time warning methods in roadside bank stability have to set the threshold value of all deformation value. Results from a sample test on a roadside bank with cohesionless soil demonstrate that this model is superior to others in accuracy and adaptability, and it meets the need of real-time monitoring engineering.关键词
交通工程/无粘性土公路边坡/稳定性安全系数Fs/变形值/神经网络法Key words
traffic engineering/ cohesionless soil roadside bank/ safety factor of stability Fs/ deformation value/ artificial neural network (ANN)分类
交通工程引用本文复制引用
王树威,陈艳艳,陈宁,赖见辉,吴克寒..基于神经网络的公路边坡稳定性实时判断[J].交通信息与安全,2013,31(2):104-108,5.基金项目
交通运输部科技项目(批准号:2012364223300)资助 （批准号:2012364223300）
