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Computational Intelligence, Theory and Applications pp 53–59Cite as

Smooth Extensions of Fuzzy If-Then Rule Bases

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Part of the book series: Advances in Soft Computing ((AINSC,volume 33))

Abstract

In order to extend fuzzy if-then rules bases, we propose to make use of a method which has been developed for the interpolation of crisp data — the multivariate spline interpolation. Among the various possibilities of how to accomplish the necessary generalisations, we describe here the probably simplest method: We apply spline interpolation to fuzzy data which itself is approximated by vectors of a finite-dimensional real linear space.

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Author information

Authors and Affiliations

  1. Department of Computer Science I, Dortmund University, 44227, Dortmund

    Thomas Vetterlein

Authors
  1. Thomas Vetterlein
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Editor information

Editors and Affiliations

  1. Department of Computer Science 1, University of Dortmund, FB 8 Ektrotechnik FB Informatik LS Informatik I, Postfach 50 05 00, 44221, Dortmund, Germany

    Bernd Reusch

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© 2005 Springer-Verlag Berlin Heidelberg

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Vetterlein, T. (2005). Smooth Extensions of Fuzzy If-Then Rule Bases. In: Reusch, B. (eds) Computational Intelligence, Theory and Applications. Advances in Soft Computing, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31182-3_5

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  • DOI: https://doi.org/10.1007/3-540-31182-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22807-3

  • Online ISBN: 978-3-540-31182-9

  • eBook Packages: EngineeringEngineering (R0)

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