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International Conference on Fuzzy Systems and Knowledge Discovery

FSKD 2005: Fuzzy Systems and Knowledge Discovery pp 179–188Cite as

A TSK Fuzzy Inference Algorithm for Online Identification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

Abstract

This paper proposes an online self-organizing identification algorithm for TSK fuzzy model. The structure of TSK fuzzy model is identified using distance. Parameters of the piecewise linear function consisting consequent part are obtained using recursive version of combined learning method of global and local learning. Both input and output spaces are considered in the proposed algorithm to identify the structure of the TSK fuzzy model. By processing clustering both in input and output space, outliers are excluded in clustering effectively. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. The proposed algorithm can obtain a TSK fuzzy model through one pass. By using the proposed combined learning method, the estimated function can have high accuracy.

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Author information

Authors and Affiliations

  1. Department of electrical and electronic engineering, Yonsei University, 134, Shinchon-dong, Sudaemoon-gu, Seoul, Korea

    Kyoungjung Kim, Eun Ju Whang, Euntai Kim & Mignon Park

  2. Korea electronics technology institute, 401-402, B/D 192, Yakdae-Dong, Wonmi-Gu, Buchon-Si, Kyunggi-Do, Korea

    Chang-Woo Park

Authors
  1. Kyoungjung Kim
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  2. Eun Ju Whang
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  3. Chang-Woo Park
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  4. Euntai Kim
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  5. Mignon Park
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, K., Whang, E.J., Park, CW., Kim, E., Park, M. (2005). A TSK Fuzzy Inference Algorithm for Online Identification. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_23

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  • DOI: https://doi.org/10.1007/11539506_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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