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Identification of Fuzzy Systems with the Aid of Genetic Fuzzy Granulation

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Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

We propose the identification of fuzzy systems with the aid of genetic fuzzy granulation to carry out the model identification of complex and nonlinear systems. The proposed fuzzy model implements system structure and parameter identification with the aid of genetic algorithms and information granulation. To identify the structure of fuzzy rules we use genetic algorithms. Granulation of information realized with Hard C-Means clustering help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method. An example is given to evaluate the validity of the proposed model.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, The University of Suwon, San 2-2 Wau-ri, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 445-743, South Korea

    Sung-Kwun Oh & Keon-Jun Park

  2. Division of Computer Engineering, Daejeon University, 96-3 Yongun-dong, Dong-gu, Daejeon, 300-716, South Korea

    Yong-Soo Kim

  3. Department of Electrical Electronic and Information Engineering, Wonkwang University, 344-2, Shinyong-Dong, Iksan, Chon-Buk, 570-749, South Korea

    Tae-Chon Ahn

Authors
  1. Sung-Kwun Oh
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  2. Keon-Jun Park
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  3. Yong-Soo Kim
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  4. Tae-Chon Ahn
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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Oh, SK., Park, KJ., Kim, YS., Ahn, TC. (2005). Identification of Fuzzy Systems with the Aid of Genetic Fuzzy Granulation. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_48

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  • DOI: https://doi.org/10.1007/11494669_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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