Application of Wavelet Neural Network Model in Runoff Prediction
Tang Ting · Water Conservancy Science and Technology and Economy · 2012
Through combining the wavelet and the BP neural network model,a new prediction method is developed for medium-long term runoff prediction.To begin with,the annual runoff series is decomposed systematically based on Mallat method.Second,low-frequency components and high frequency components which decomposed of different scales were reconstructed to Mallat algorithm.And finally,the factored series are used to forecast with the BP neural network model.This paper is applied to annual runoff prediction in Sanmenxia station of Yellow River by 1470 to 2002 to predict and test,which is compared with traditional BP neural network.The results show that wavelet neural network model is effective in practice,and also improves the forecasting precision.