%0 Journal Article
%T LS-SVM parameters selection based on genetic algorithm and its application in economic forecasting<br>基于遗传算法的LS-SVM参数优选及其在经济预测中的应用
%A ZHOU Hui-ren
%A ZHENG Pi-e
%A ZHAO Chun-xiu
%A <br>周辉仁
%A 郑丕谔
%A 赵春秀
%J 计算机应用
%D 2007
%I 
%X It was proposed that genetic algorithm was used to optimize parameters of Least Squares Support Vector Machine (LS-SVM) and LS-SVM was well trained by using population data in an economic system. Then, the well trained LS-SVM was used to forecast population in a city. Finally, LS-SVM and BP network were compared in prediction and the result shows that the genetic algorithm for optimizing parameters of Least Squares Support Vector Machine proposed in this paper is feasible and effective.
%K Least Squares Support Vector Machines (LS-SVM)
%K genetic algorithm
%K optimization of hyper-parameters
%K economic prediction<br>最小二乘支持向量机
%K 遗传算法
%K 参数优化
%K 经济预测
%K 基于遗传算法
%K 参数优选
%K 经济预测
%K 应用
%K forecasting
%K economic
%K application
%K genetic
%K algorithm
%K based
%K selection
%K 方法
%K 精确度
%K 模型
%K 预测结果
%K 比较
%K 网络
%K 人口数据
%K 城市
%K 训练
%K 经济系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512215D180CC0C609F0&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=782B98DFA363AFCB&eid=8EA44A8F6C7F424F&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=5