Chaotic System Identification Based on BP Neural Network of Two Order Particle Swarm Optimization
二阶微粒群优化神经网络的混沌系统辨识方法

Aiming to the shortage of BP neural network in training algorithm,the problem of neural network learning can be seen as a function optimization problem and the neural network model based on two order particle swarm optimization is proposed.Then,chaotic system is identified by BP trained with two-order PSO and the efficiency of BP trained with two-order PSO is compared with those of BP and RBF based on the identification of chaotic system.The experimental results show that BP trained with two-order PSO is better than BP and RBF used in chaotic system identification.