路基工程Issue(5)：164-169,6.DOI:10.13379/j.issn.1003-8825.2017.05.36
PSO-BP神经网络在隧道围岩变形预测中的应用
Application of PSO-BP Neural Network in Prediction of Tunnel Rock Deformation
李海斌 1翟秋柱 1张优 2王亚暐 3张霄3
作者信息
- 1. 中铁十七局集团第四工程有限公司,重庆401121
- 2. 中国中铁西南科学研究院,成都610000
- 3. 西南交通大学地球科学与环境工程学院,成都610000
- 折叠
摘要
Abstract
In relation to the prediction of rock deformation surrounding tunnel under complicated geological conditions in western Yunnan,this paper on the basis of BP neural network introduced an improved particle swarm optimization (PSO) to find out PSO-BP neural network by debugging and improving.This neural network,which combines the PSO global searching ability with the BP local searching ability,has strong capability of nonlinear mapping and generalization with certain capability of fault tolerance.The result of calculation shows that PSO-BP neural network is of high accuracy with the average absolute error of 2.4 mm and the average relative error of 2.7 ％,and meets the requirement of rock deformation prediction.关键词
隧道工程/围岩变形预测/粒子群算法/PSO-BP神经网络Key words
tunneling engineering/prediction of rock deformation/particle swarm optimization/PSO-BP neural network分类
交通工程引用本文复制引用
李海斌,翟秋柱,张优,王亚暐,张霄..PSO-BP神经网络在隧道围岩变形预测中的应用[J].路基工程,2017,(5):164-169,6.
