Mobile Communications Customer Churn Prediction Algorithm Based on Improved GA-BP Network

doi:10.12068/j.issn.1005-3026.2019.02.006

Abstract

Abstract: A customer churn prediction model based on BP neural network(BPNN)has achieved well enough results. However， it has relatively weak global search ability and is very sensitive to the initial network weights. A prediction algorithm based on improved genetic algorithm(IGA)and BPNN(IGA-BP)is proposed by analyzing users’communication behavior， where the weights and thresholds of BPNN are initialized with IGA， thus improving the accuracy of the prediction model. The improved algorithm adopts a self-adapting probability of crossover and mutation， which enhances the global optimum search ability of GA. The proposed IGA-BP model has obvious improvement on customer churn prediction， compared with existing algorithms.

Key words: mobile communication, behavior analysis, customer churn, BP neural network, genetic algorithm

CLC Number:

TP18

YU Rui-yun， XUE Lin， AN Xuan-miao， XIA Xing-you. Mobile Communications Customer Churn Prediction Algorithm Based on Improved GA-BP Network[J]. Journal of Northeastern University Natural Science, 2019, 40(2): 180-185.

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