小波神经网络在柴河水库坝基渗流量预测中的应用  

Application of wavelet neural network to forecast of dam foundation seepage for Chaihe Reservoir

作　　者：闫滨[1] 李东艳[1] 

机构地区：[1]沈阳农业大学水利学院,辽宁沈阳110161

出　　处：《水利水电技术》2009年第3期71-73,共3页Water Resources and Hydropower Engineering

基　　金：沈阳农业大学青年基金(20070110)

摘　　要：小波神经网络是基于小波变换与人工神经网络的一种前馈型神经网络。文中将小波神经网络模型应用于柴河水库右坝段坝基渗流量的预测,利用实测资料对其模拟计算结果进行检验。通过与BP神经网络模型的预测结果比较,证明小波网络模型的收敛速度更快、预测精度更高。Wavelet neural network is a feed forward neural network based on wavelet transform and artificial neural network.The wavelet neural network model is applied herein to forecast the seepage of the right dam foundation of Chaihe Reservoir,and then the simulation result is checked with the observed data.Based on the comparison with the forecast result from BP neural network,it is demonstrated that the convergence speed of the wavelet neural network is faster with more accurate precision.

关 键 词：小波神经网络 坝基渗流 安全监测 柴河水库 

分 类 号：TV223.4[水利工程—水工结构工程]