An Improved BP Neural Network Algorithm and Its Application in Customer Classification

Abstract

BP neural network is wildly used in various disciplines for its powerful simulation calculation ability in recent years but the shortages such as low convergence limits its usage in practice. An improved BP neural network algorithm is presented for customer classification based on analyzing the working principles in the paper. First, through analyzing the actual characteristics of network customers, a new customer classification indicator system including 12 customer classification indicators is designed; Then, when considering the advantages of high classification accuracy of BP neural network model, and in order to speed up the convergence of the model, the paper improves BP neural network model through improving its trigonometric function, type function and additional momentum to classify customers for customer relationship management. Finally, the model is realized by the data from certain E-commerce enterprise to carry out customer classification and the experimental results indicate that the model has favorable classification results.