1. Proceedings of the 7th
World Congress on Intelligent Control and Automation
June 25 - 27, 2008, Chongqing, China
Particle Swarm Optimization based RBF Neural
Networks Learning Algorithm
Qi Kang1, Jing An2, Dongsheng Yang1,3, Lei Wang1, Qidi Wu1
1)
College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China
(E-mail: kangqi_kz@hotmail.com)
2)
Shanghai Institute of Technology, Shanghai 200235, China (E-mail: anjing_tj@163.com)
3)
Shanghai Municipal Informatization Commission, Shanghai 200040, China
Abstract—Swarm intelligence optimization is introduced into RBF neural networks training in this paper, a novel RBF
neural networks learning algorithm based on particle swarm optimization is presented, and validated through numerical
simulation. Finally, the unite framework of this RBF algorithm based on natural-inspired computation is proposed.
Keywords— Particle Swarm Optimization, RBF Neural Networks, Natural-inspired Computation
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[6] Kennedy J, Eberhart R C, “Particle swarm optimization,” Proc.
IEEE International Conf. on Neural Networks. Piscataway:
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IEEE, Perth, 1995, pp 1942-1948.
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[7] Eberhart R C, Shi Y, “Particle swarm optimization: developments,
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applications and resources,” Proc. Congress on Evolutionary
Computation. Piscataway: IEEE, Soul, 2001. 81-86
[8] Wang L, Kang Q, Wu Q.D, “Nature-inspired computation:
effective realization of artificial intelligence,” System
362
Engineering Theory and Practice, 2007, 27 (5): 126-13
610
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