%0 Journal Article
%T Variables Screening Methods Based on the Optimization of RBF Neural Network<br>基于优化的RBF 神经网络的变量筛选方法
%A XU Fu-Qiang
%A LIU Xiang-Guo
%A <br>徐富强
%A 刘相国
%J 计算机系统应用
%D 2012
%I 
%X Because of the Characteristics of RBF neural network structure is simple, output and initialized weights irrelevant, adaptive, less adjustable parameter etc. This paper proposes using the method of cross validation to find the optimal parameter value of SPREAD, constructs the optimal RBF neural network model and combines the algorithm of MIV to use for variables screening. Through the example test the validity of the model, also make the method has better ability of stability and applied.
%K RBF neural network
%K parameter optimization
%K cross validation method
%K MIV
%K variables screening<br>RBF神经网络
%K 参数优化
%K 交叉验证法
%K MIV
%K 变量筛选
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA0537A2E62A2626C4BB14&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=38B194292C032A66&sid=9F6DA927E843CD50&eid=3D9746C06EC12B45&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7