Selective neural network ensemble methods based on chaos PSO

Abstract

Selective Neural Network Ensemble(NNE) methods based on Decimal Particle Swarm Optimization(DePSO) and Binary Particle Swarm Optimization(BiPSO) were proposed in this paper.The basic idea of the methods was to optimally select Neural Networks(NNs) to construct NNE with the aid of PSO.This may maintain the diversity of NNs and decrease the effect of collinearity and noise of sample.Meanwhile,chaos mutation was adopted in order to increase the diversity of particles of PSO.The experimental results show that the chaos PSO algorithm is an effective ensemble method,and it may improve the generalization ability of NNE in comparison with the available ones.