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Learning Fuzzy Rules with Evolutionary Algorithms — An Analytic Approach

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Book cover Parallel Problem Solving from Nature – PPSN X (PPSN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5199))

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Abstract

This paper provides an analytical approach to fuzzy rule base optimization. While most research in the area has been done experimentally, our theoretical considerations give new insights to the task. Using the symmetry that is inherent in our formulation, we show that the problem of finding an optimal rule base can be reduced to solving a set of quadratic equations that generically have a one dimensional solution space. This alternate problem specification can enable new approaches for rule base optimization.

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Author information

Authors and Affiliations

  1. School of Mathematics, University of Adelaide, Adelaide, SA 5005, Australia

    Jens Kroeske

  2. School of Computer Science, University of Adelaide, Adelaide, SA 5005, Australia

    Adam Ghandar & Zbigniew Michalewicz

  3. Institute of Computer Science, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warsaw, Poland

    Zbigniew Michalewicz

  4. Polish-Japanese Institute of Information Technology, ul. Koszykowa 86, 02-008, Warsaw, Poland

    Zbigniew Michalewicz

  5. Max-Planck-Institut für Informatik, 66123 Saarbrücken, Germany

    Frank Neumann

Authors
  1. Jens Kroeske
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  2. Adam Ghandar
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  3. Zbigniew Michalewicz
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  4. Frank Neumann
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Editor information

Editors and Affiliations

  1. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

  2. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Thomas Jansen  & Nicola Beume  & 

  3. Department of Computing and Electronic Systems, University of Essex, CO4 3SQ, Colchester, Essex, UK

    Simon Lucas

  4. Dipartimento di Ingegneria Meccanica, Università degli Studi di Trieste, 34127, Trieste, Italy

    Carlo Poloni

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© 2008 Springer-Verlag Berlin Heidelberg

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Kroeske, J., Ghandar, A., Michalewicz, Z., Neumann, F. (2008). Learning Fuzzy Rules with Evolutionary Algorithms — An Analytic Approach. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_104

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  • DOI: https://doi.org/10.1007/978-3-540-87700-4_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87699-1

  • Online ISBN: 978-3-540-87700-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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