English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 56562/90363 (63%)
造访人次 : 11859310      在线人数 : 71
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/100117


    题名: Fingerprint recognition by multi-objective optimization PSO hybrid with SVM
    作者: Hsieh, Ching-Tang;Hu, Chia-Shing
    贡献者: 淡江大學電機工程學系
    关键词: MOPSO-CD;SVM;fingerprint recognition
    日期: 2014-12-01
    上传时间: 2015-01-28 11:08:03 (UTC+8)
    出版者: Mexico: Universidad Nacional Autonoma de Mexico * Centro de Ciencias Aplicadas y Desarrollo Tecnologico
    摘要: Researchers put efforts to discover more efficient ways to classification problems for a period of time. Recent years,the support vector machine (SVM) becomes a well-popular intelligence algorithm developed for dealing this kind of problem. In this paper, we used the core idea of multi-objective optimization to transform SVM into a new form. This form of SVM could help to solve the situation: in tradition, SVM is usually a single optimization equation, and parameters for this algorithm can only be determined by user’s experience, such as penalty parameter. Therefore, our algorithm is developed to help user prevent from suffering to use this algorithm in the above condition. We use multiobjective Particle Swarm Optimization algorithm in our research and successfully proved that user do not need to use trial – and – error method to determine penalty parameter C. Finally, we apply it to NIST-4 database to assess our proposed algorithm feasibility, and the experiment results shows our method can have great results as we expect.
    關聯: Journal of Applied Research and Technology 12(6), pp.1014-1024
    DOI: 10.1016/S1665-6423(14)71662-1
    显示于类别:[電機工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 大小格式浏览次数
    index.html0KbHTML199检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈