Hybrid Recursive Particle Swarm Optimization Learning Algorithm in the Design of Radial Basis Function Networks

Ching-Yi Chen ； Hsuan-Ming Feng ； Fun Ye

《Journal of Marine Science and Technology》 15卷1期 (2007/03) Pp. 31-40

https://doi.org/10.6119/JMST.200703_15(1).0005

並列摘要

In this paper, an innovative hybrid recursive particle swarm optimization (HRPSO) learning algorithm with normalized fuzzy c-mean (NFCM) clustering, particle swarm optimization (PSO) and recursive least-squares (RLS) is proposed to generate radial basis function networks (RBFNs) modeling system with small numbers of descriptive radial basis functions (RBFs) for fast approximating two complex and nonlinear functions. Simulation results demonstrate that the generated NFCM-based learning schemes approach the desired modeling systems within the smaller population sizes.

並列關鍵字

normalized fuzzy c-means ； particle swarm optimization ； recursive least-squares ； radial basis function networks