%0 Journal Article
%T Coupling GA with SVM for feature selection in high-resolution remote sensing target recognition<br>面向遥感目标识别耦合GA与SVM的特征优选方法
%A SUN Ning
%A CHEN Qiuxiao
%A LUO Jiancheng
%A SHEN Zhanfeng
%A HU Xiaodong
%A <br>孙宁
%A 陈秋晓
%A 骆剑承
%A 沈占锋
%A 胡晓东
%J 遥感学报
%D 2010
%I 
%X As one of the key techniques for high-resolution remote sensing target recognition, feature selection focused on how to find the critical features in the feature set to represent the target. Generally, the classical methods for feature selection were as follows, principal component analysis, empirical method, etc. When using these classical methods, recognition accuracy was not guaranteed. In this paper, a new method was proposed, the main idea of which was to couple GA (Genetic Algorithm) and SVM (Support Vector Machine) for feature selection, and using recognition results to guide the revolution direction of GA. Meanwhile, to reduce the risk of premature convergence of the traditional GA, some modification had been made. The experi-ment demonstrated the effectiveness of the proposed method.
%K genetic algorithm
%K support vector machine
%K target recognition
%K feature selection<br>遗传算法
%K 支持向量机
%K 目标识别
%K 特征优选
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=8B9DCD2271E65324EF87E3AB65885DB8&yid=140ECF96957D60B2&vid=F3583C8E78166B9E&iid=94C357A881DFC066&sid=66973F362693F62B&eid=114891522AE71A91&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=13