%0 Journal Article
%T Structure learning method studying of stochastic fuzzy neural network<br>随机模糊神经网络的结构学习算法研究
%A ZHANG Jun
%A L Jing-jing
%A <br>张骏
%A 吕静静
%J 计算机应用
%D 2005
%I 
%X Based on input layer, latent layer and output layer correlation rule, the structure learning method ot stoclaastic fuzzy neural network considered the effects on the latent layer function, which was very important for engineering applications. One key problem of this algorithm is how to get the best node number of latent layer. In this paper, a normal method to confirm the best node number was proposed. According to this theory, one simulation was presented.
%K stochastic fuzzy neural network
%K parameter learning
%K node number of latent layer<br>随机模糊神经网络
%K 参数学习
%K 隐层节点数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=C6EC5767A9D3DF6A&yid=2DD7160C83D0ACED&vid=C5154311167311FE&iid=F3090AE9B60B7ED1&sid=764CFDBFE956EAB0&eid=45DD1A078A51A2E3&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=4