关键词: 粒子群, 减聚类算法, 混沌时间序列, 最小二乘法, 径向基函数神经网络

Abstract: A method of radial basis function(RBF) neural network algorithm based on particle swarm optimization(PSO) algorithm. The first to determine units’ number in RBF layer using subtractive clustering method, the second to optimize central position and directional width based on PSO algorithm, and the last to train RBF neural network combine with least-square method. The new training algorithm is used to predict chaotic time series, and the simulation results are efficiency.

Key words: particle swarm optimization, subtractive clustering method, chaotic time series, least-square method, RBF neural network