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Application of the General Gaussian Membership Function for the Fuzzy Model Parameters Tunning

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

A system input-output response is modeled using a knowledge-based method of signal processing known as neuro-fuzzy logic. The paper presents a new method of the fuzzy model parameters tunning. Fuzzy model tuning procedures based on an evolutionary algorithm are also given. As an example, the analysis of the membership function kind is carried out for the fuzzy modeling of parameters, which are necessary to describe the state of a pressure vessel with water-steam mixture during accidental depressurizations.

This work was supported by the EU FP5 project DAMADICS and in part by the State Committee for Scientific Research in Poland (KBN)

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Author information

Authors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, Podgórna 50 Str., 65-246, Zielona Góra, Poland

    Andrzej Pieczyński & Andrzej Obuchowicz

Authors
  1. Andrzej Pieczyński
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  2. Andrzej Obuchowicz
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Pieczyński, A., Obuchowicz, A. (2004). Application of the General Gaussian Membership Function for the Fuzzy Model Parameters Tunning. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_50

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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