%0 Journal Article
%T Improved Global K-Means and Its Application in Beer System<br>改进的全局K 均值算法及其在啤酒系统中的应用
%A ZHANG Zhong-Hou
%A ZHAO Long
%A <br>张忠厚
%A 赵龙
%J 计算机系统应用
%D 2012
%I 
%X K-means algorithm has been limited by the main questions which are the problems to determine the number of clusters, initial cluster center points of selection and to avoid isolating the problem. To solve these problems the algorithm has been improved in this paper and the paper has applied the improved algorithm and dynamic recurrent fuzzy neural network to the beer fermentation systems. Because of complex neural network structure, the particle swarm optimization algorithm can be used to optimize connected network structure of the connection weights between layers and the network topology. This PSO does not easily trapped local minima and has better generalization ability. At the same time, in practical application the principle of improved PSO algorithm is simple and has less parameter so that it＇s easier to realize.
%K AI
%K PSO
%K K-means
%K predictive control
%K DRFNN<br>人工智能
%K 粒子群优化算法
%K K均值
%K 预测控制
%K DRFNN
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA05372A76BABE7AE8DD2D&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=5D311CA918CA9A03&sid=5D9D6A8FC2C66FD8&eid=F983DCE5FC8D49E2&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=9