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Fuzzy Support Vector Classification Based on Fuzzy Optimization

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Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence (ICIC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5755))

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Abstract

This paper is concerned with the fuzzy support vector classification, in which both of the type of the output training point and the value of the final fuzzy classification function are triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, we transform this programming into its equivalence quadratic programming. Final, a fuzzy support vector classification algorithm is proposed to deal with the problem. An example is presented to illustrate rationality of the algorithm.

Supported by National Natural Science Pivot Foundation of China (No.10631070) and Natural Science Foundation of Zhejiang Province (No.Y606082).

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Author information

Authors and Affiliations

  1. Zhijiang College, Zhejiang University of Technology, Hangzhou, P.R. China, 310024

    Zhimin Yang & Bingquan Zhang

  2. College of Business and Administration, Zhejiang University of Technology, Hangzhou, P.R. China, 310023

    Xiao Yang

Authors
  1. Zhimin Yang
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  2. Xiao Yang
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  3. Bingquan Zhang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, China

    De-Shuang Huang

  2. Graduate School of Electrical Engineering, University of Ulsan, Korea, San 29, Mugeo-Dong, Nam-Ku, 680 - 749, Ulsan, Korea

    Kang-Hyun Jo

  3. School of Electrical Engineering, University of Ulsan, Ulsan, South Korea

    Hong-Hee Lee

  4. School of Electrical Engineering, University of Ulsan, South Korea

    Hee-Jun Kang

  5. e.B.I.S. s.r.l. (electronic Business in Security), Spin-Off of Polytechnic of Bari, Str. Prov. per Casamassima Km., 3, 70010, Valenzano, (BA), Italy

    Vitoantonio Bevilacqua

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© 2009 Springer-Verlag Berlin Heidelberg

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Yang, Z., Yang, X., Zhang, B. (2009). Fuzzy Support Vector Classification Based on Fuzzy Optimization. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_15

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  • DOI: https://doi.org/10.1007/978-3-642-04020-7_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04019-1

  • Online ISBN: 978-3-642-04020-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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