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International Conference on Computational and Information Science

CIS 2005: Computational Intelligence and Security pp 544–549Cite as

Input Selection for Support Vector Machines Using Genetic Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

Abstract

In this paper, an effective and simple method of input selection for nonlinear regression modeling using Support Vector Machine combined with Genetic Algorithm is proposed. Genetic Algorithm is used in order to extract dominant inputs from a large number of potential inputs in input selection process. Support Vector Machine is used as a nonlinear regressor with the selected dominant inputs. The proposed method is applied to the Box-Jenkins furnace benchmark to verify its effectiveness.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Korea University, Seoul, Korea

    Hee-Jun Song & Seon-Gu Lee

  2. Dept. of Environmental Science & Engineering, Ewha Woman’s Univ., Seoul, Korea

    Sung-Hoe Huh

Authors
  1. Hee-Jun Song
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  2. Seon-Gu Lee
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  3. Sung-Hoe Huh
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Song, HJ., Lee, SG., Huh, SH. (2005). Input Selection for Support Vector Machines Using Genetic Algorithms. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_79

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  • DOI: https://doi.org/10.1007/11596448_79

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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