关键词: 中心聚类, 微粒群优化, 径向基函数, 递推最小二乘, 转鼓强度

Abstract: An algorithm for designing Radial Basis Function Neural Network based on center clustering and modified particle swarm optimization algorithm is introduced.Center clustering algorithm is proposed to process the input sample，and adaptively specify the hidden layer parameters of RBF neural network；classic PSO algorithm（Particle Swarm Optimization） with modified calculation method about globally optimal solution is used to train the parameters，and makes them tend to global optima；the output layer weights are updated on line by recursive least square algorithm with forgetting factor.At last，the hybrid algorithm is applied to design the prediction model about relationship between the sinter composition and drum strength.Then experiment validates the model with new data which are collected from sinter workshop.Experimental results show that the hybrid algorithm has high convergence speed，and model built by that has great prediction precision.

Key words: center clustering, Particle Swarm Optimization（PSO）, Radial Basis Function（RBF）, recursive least square, drum strength