[1]李素,袁志高,王聪,等.群智能算法优化支持向量机参数综述[J].智能系统学报,2018,(01):70-84.[doi:10.11992/tis.201707011]
 LI Su,YUAN Zhigao,WANG Cong,et al.Optimization of support vector machine parameters based on group intelligence algorithm[J].CAAI Transactions on Intelligent Systems,2018,(01):70-84.[doi:10.11992/tis.201707011]
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群智能算法优化支持向量机参数综述(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2018年01期
页码:
70-84
栏目:
出版日期:
2018-01-24

文章信息/Info

Title:
Optimization of support vector machine parameters based on group intelligence algorithm
作者:
李素1 袁志高1 王聪2 陈天恩2 郭兆春1
1. 北京工商大学 食品安全大数据技术北京市重点实验室, 北京 100048;
2. 国家农业信息化工程技术研究中心, 北京 100097
Author(s):
LI Su1 YUAN Zhigao1 WANG Cong2 CHEN Tianen2 GUO Zhaochun1
1. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;
2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
关键词:
支持向量机统计学习群智能参数优化全局寻优并行搜索收敛速度寻优精度
Keywords:
support vector machinestatistical studygroup intelligence algorithmoptimization of parametersglobal optimizationparallel searchconvergence speedoptimization accuracy
分类号:
TP181
DOI:
10.11992/tis.201707011
摘要:
支持向量机建立在统计学习的理论基础之上,具有理论的完备性,但是在应用上仍然存在模型参数难以选择的问题。首先,介绍了支持向量机和群智能算法的基本概念;然后,系统地叙述了各种经典的群智能算法进行支持向量机参数优化取得的最新研究成果以及总结了优化过程中存在的问题和解决方案;最后,结合该领域当前研究现状,提出了群智能算法优化支持向量机参数研究中需要关注的问题,展望了这一研究方向在未来的发展趋势和前景。
Abstract:
The support vector machine is based on statistical learning theory, which is complete, but problems remain in the application of model parameters, which are difficult to choose. In this paper, we first introduce the basic concepts of the support vector machine and the group intelligence algorithm. Then, to optimize the latest research results and summarize existing problems and solutions, we systematically describe various classical group intelligence algorithms that the support vector machine parameters identified. Finally, drawing on the current research situation for this field, we identify the problems that must be addressed in the optimization of support vector machine parameters in the group intelligence algorithm and outline the prospects for future development trends and research directions.

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备注/Memo

备注/Memo:
收稿日期:2017-07-06。
基金项目:国家自然科学基金项目(31101088,91546112);北京市教育委员会科技计划面上项目(KM201310011010).
作者简介:李素,女,1976年生,副教授,博士,主要研究方向为群智能算法、智能信息处理。主持国家自然科学基金子项目1项、北京市教委科技面上项目1项;主持教育部重点实验室开放基金1项,中科院地理所横向项目1项;参与国家自然科学基金1项、省部级项目多项、横向项目多项。发表学术论文30余篇,出版学术专著2部,授权软件著作权多项;袁志高,男,1994年生,硕士研究生,主要研究方向为机器学习;王聪,女,1989生,高级工程师,主要研究方向为地理信息系统、农业云服务平台。参与北京市科委计划项目、北京市自然科学基金重点项目等近10个项目,获得专利2项、软件著作权15项,发表论文多篇,被EI检索2篇,SCI检索1篇。
通讯作者:陈天恩.E-mail:chente@nercita.org.cn.
更新日期/Last Update: 2018-02-01