人民黄河2016，Vol.38Issue(11)：136-139,4.DOI:10.3969/j.issn.1000-1379.2016.11.033
基于AFSA-灰色神经网络模型的大坝裂缝预测
Prediction of Dam Cracks Based on AFSA-Grey Neural Network
游健 1金葵 2姜彦作3
作者信息
- 1. 云南省水利水电勘测设计研究院，云南 昆明650000
- 2. 云南省电力学校，云南 昆明650000
- 3. 河海大学 水资源高效利用与工程安全国家工程研究中心，江苏 南京210098
- 折叠
摘要
Abstract
When grey neural network predicts relevant issues, the predictive accuracy of grey neural network may be lower because of artifi⁃cial random initial parameter of grey neural network. Aiming at solving the problem, the paper applied artificial fish swarm algorithm to optimize the parameter of grey neural network,and proposed artificial fish swarm algorithm⁃grey neural network,making used of the model to predict the crack width of dam. Comparing with the predictive result of BP neural network and traditional grey neural network, the artificial fish swarm algorithm⁃grey neural network could improve the predictive accuracy. The predict method named artificial fish swarm algorithm⁃grey neural network is better to predict the propagation of dam crack width and could keep the stability of predictive process. As a result, the method can be applied to predict the crack width of dam.关键词
大坝/裂缝开度预测/人工鱼群/灰色神经网络/BP神经网络Key words
dam/crack width prediction/artificial fish/grey neural network/BP neural network分类
建筑与水利引用本文复制引用
游健,金葵,姜彦作..基于AFSA-灰色神经网络模型的大坝裂缝预测[J].人民黄河,2016,38(11):136-139,4.
