关键词: 神经网络, 混沌系统, 粒子群优化算法, 系统辨识

Abstract: BP is the most commonly used artificial neural networks，but it suffers from extensive computations，relatively slow convergence speed and other possible weaknesses for complex problems.Genetic Algorithm(GA)has been successfully used to train neural networks，but often with the result of exponential computational complexities and hard implementation.Hence Particle Swarm Optimization(PSO)is used to train BP in the paper.The efficiency of BP trained with PSO is compared with those of BP and BP trained with GA based on the identification of chaotic system.Comparison based on the searching precision and convergence speed of each method shows that BP trained with PSO is dominant and effective to identify chaotic system.

Key words: neural networks, chaotic system, particle swarm optimization, system identification