水力发电2017，Vol.43Issue(3)：68-71,105,5.
基于进化神经网络模型的面板堆石坝沉降和面板挠度预测
Settlement and Slab Deflection Prediction of Concrete Face Rockfill Dam Based on Evolutionary Neural Network Model
摘要
Abstract
The estimation of the deformation of rockfill dam and slab deflection has vital significance to instruct the design and construction of rockfill dam.In view of the differences of rockfill dam's parameter between indoor test and practical engineering and the rockfill dam that preparing for construction lack of measured deformation data to parameter feedback,the monitoring data of similar constructed concrete face rockfill dam are widely collected,and then the genetic algorithm and neural network model are combined to establish evolutionary neural network model for deformation prediction of rockfill dam engineering.Taking dam height,aspect ratio and dry density of concrete face rockfill dam that preparing for construction as control parameters,the deformation and slab deflection can be obtained through the evolutionary neural network model which being trained.The example analysis shows that the method is feasible.关键词
遗传算法/进化神经网络模型/沉降变形/面板挠度/预测Key words
genetic algorithm/evolutionary neural network model/settlement and deformation/slab deflection/prediction分类
建筑与水利引用本文复制引用
赵新瑞,吕晓曼,黄耀英,左全裕,刘钰..基于进化神经网络模型的面板堆石坝沉降和面板挠度预测[J].水力发电,2017,43(3):68-71,105,5.基金项目
国家自然科学基金资助项目(51209124) （51209124）
