Applied research of BP neural network with feedback input
Xiang Ren · Jisuanji gongcheng yu sheji · 2010
To effectively solve the accuracy problem of the hydrological forecasting with non-linear characteristics,by learning and researching the back-propagation BP neural network,analyzing the mutual information between the variables,the concept of the related information entropy between the systems is proposed,and a self-iterative back-propagation neural network model suitable for hydrological forecast is set up.This model improved the deficiency of the traditional BP algorithm greatly by correcting the iterative factor timely,adjusting the weights and thresholds of the network constantly in the back-propagation progress.Finally,this method increased the forecast accuracy.In the applied research,the forecast result of the self-iterative back-propagation model is better than the traditional one.