基于遗传算法的回归型支持向量机参数选择法

计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (7): 23-26.

基于遗传算法的回归型支持向量机参数选择法

李良敏^1,3,温广瑞²,王生昌³

1.长安大学汽车运输安全保障技术交通行业重点实验室，西安 710064
2.西安交通大学机械制造系统工程国家重点实验室，西安 710049
3.长安大学汽车学院，西安 710064

收稿日期:2007-10-26 修回日期:2007-12-06 出版日期:2008-03-01 发布日期:2008-03-01
通讯作者: 李良敏

Parameters selection of support vector regression based on genetic algorithm

LI Liang-min^1,3,WEN Guang-rui²,WANG Sheng-chang³

1.Key Laboratory of Automotive Transportation Safety Enhancement Technology of the Ministry of Communication，Chang’an University，Xi’an 710064，China
2.State Key Laboratory for Manufacturing Systems Engineering，Xi’an Jiaotong University，Xi’an 710049，China
3.School of Automobile，Chang’an University，Xi’an 710064，China

Received:2007-10-26 Revised:2007-12-06 Online:2008-03-01 Published:2008-03-01
Contact: LI Liang-min

摘要/Abstract

摘要： 研究了遗传算法在回归型支持向量机参数选择中的应用：首先，分析了支持向量机的几个参数对其预报能力的影响，发现参数选取不当，会导致支持向量机出现过学习或欠学习现象；在此基础上提出利用遗传算法来解决回归型支持向量机的参数选择问题，模拟实验证明，该方法克服了传统参数选择方法存在的缺点，提高了支持向量机的预报精度。

Abstract: This paper mainly deals with the application of genetic algorithm to parameters selection of support vector regression.The variability in predict performance of support vector regression with respect to the free parameters is firstly investigated.A conclusion is drawn that improper parameter would lead to overfitting or underfitting.Then the genetic algorithm is introduced to select parameters for support vector regression.Simulation results proved that the proposed method overcame some obstacles of traditional parameter selection methods，thus the predict precision of support vector regression is enhanced.

李良敏^1,3,温广瑞²,王生昌³. 基于遗传算法的回归型支持向量机参数选择法[J]. 计算机工程与应用, 2008, 44(7): 23-26.

LI Liang-min^1,3,WEN Guang-rui²,WANG Sheng-chang³. Parameters selection of support vector regression based on genetic algorithm[J]. Computer Engineering and Applications, 2008, 44(7): 23-26.