人民黄河Issue(10)：126-128,3.DOI:10.3969/j.issn.1000-1379.2014.10.038
遗传小波神经网络在大坝变形预测中的应用
Application of Wavelet Neural Network Model Based on Genetic Algorithm in the Prediction of Dam Deformation
摘要
Abstract
Aiming at the demerits of traditional mathematical statistical model couldn’t completely describe the nonlinear mapping relationship be-tween the dam displacement and various load factors,we introduced wavelet neural network model based on genetic algorithm to have a global opti-mization search for WNN’s initial weights and scale factor,the disadvantages that the net training might be easily fallen into local minimums and the BP neural network’s initialization was random could be avoided. This model was used in forecasting the radial displacement and tangential dis-placement of the dam,the results show that the genetic wavelet neural network’s structure stability is better,compared with BP neural network and wavelet neural network ,its prediction accuracy has improved greatly.关键词
大坝变形/遗传小波神经网络/BP 神经网络/小波神经网络/预测精度Key words
dam displacement/genetic wavelet neural network/BP neural network/wavelet neural network/prediction accuracy分类
建筑与水利引用本文复制引用
胡纪元,鸿雁,周吕,陈冠宇..遗传小波神经网络在大坝变形预测中的应用[J].人民黄河,2014,(10):126-128,3.基金项目
国家自然科学基金资助项目（41071294）；广西“八桂学者”岗位专项经费资助项目；广西空间信息与测绘重点实验室资助课题（桂科能130511402，1207115-06）；广西矿冶与环境科学实验中心资助课题（KH2012ZD004）；广西研究生教育创新计划项目（YCSZ2014151）。 （）
