An optimized process neural network model

Abstract

In this paper, we proposed an optimized process neural network based on fourier orthogonal base function, which can deal with both static value and time-varied continuous value simultaneously. To further improve its performance, we optimize the network topological structure, which adopts fourier expansion based preprocessing. Experiments based on the real datasets show that our proposed churn prediction method has better maneuverability and performance. Most important of all, our method has been used in real applications in China Mobile which is the major telecommunication company of the world. © Springer-Verlag Berlin Heidelberg 2007.