%0 Journal Article
%T Chaotic System Identification Based on BP Neural Network of Two Order Particle Swarm Optimization<br>二阶微粒群优化神经网络的混沌系统辨识方法
%A ZHANG Kun
%A LIANG Lin
%A <br>张坤
%A 梁林
%J 计算机系统应用
%D 2012
%I 
%X 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.
%K chaos
%K neural network
%K particle swarm optimization
%K two-order particle swarm optimization<br>混沌
%K 神经网络
%K 微粒群算法
%K 二阶微粒群算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA0537E69B1E24666E10CA&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=94C357A881DFC066&sid=BC084ACE66B62CC8&eid=02DC3A182A5530DF&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=10