The Improvement of BP Artificial Neural Network Algorithm and Its Application

This paper is connected with the problem of selecting architectural parameters and learning rate of BP artificial neural network. The self-adapting algorithm of BP artificial neural network has been proposed, and the corresponding C language procedure is programmed. It can make the selection of input units, hidden units and learning rate easily in the course of training, reduce external interference and improve the adaptive ability of BP neural network. Our conclusion shows that the self-adapting algorithm of BP artificial neural network superior to the statistical modeling approach and the traditional BP artificial neural network, it can not only exactly imitate training valuation but also make prediction accurately.