An enhanced swarm intelligence based training algorithm for RBF neural networks in function approximation

摘要

This paper is dedicated to the presentation of enhanced swarm intelligence based training algorithm for Radial basis functions neural networks. The proposed training algorithm (ABC-PP) is hybridization between the Artificial Bees Colony (ABC) and a predator and prey behavior to improve the diversification mechanism of the ABC. Statistical analysis is carried out with nonparametric tests to evaluate the proposed training algorithm comparing it with ABC, GA and PSO based RBF training algorithms in function approximation. The proposed algorithm is applied to identify a real inverted pendulum model giving acceptable results.