LVQ Neural Network Classification Algorithm Based on Dimension Reduction by GA

摘要：

This paper describes a dimension reduction method of input vector to improve classification efficiency of LVQ neural network,where GA is used to decrease the redundancy of input data.And in order to solve the initial weight vector sensitivity,GA is also employed to optimize the initial vector.The experimental results on the LCI data sets demonstrate that the efficiency and accuracy of our LVQ network by GA is higher than general LVQ neural network classification algorithm.

关键词： LVQ GA Dimension Reduction Classification

作者: SUN Hao WANG Ting LV Gang

作者单位: College of Mobile telecommunication Chongqing University of Post and Telecommunications Chongqing,Ch Chongqing LV Zhou Technological Co.LTD Chongqing,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 209-212

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）