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Information Criterions Applied to Neuro-Fuzzy Architectures Design

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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

In this paper we present results of application of information cirterions to neuro-fuzzy systems (NFS) design. The criterions come from autoregression estimation theory and are employed to describe the level of NFS quality. Based on this method the preferred size of systems is determined. Various criterions are compared and discussed.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Częstochowa University of Technology, Al. Armii Krajowej 36, 42-200, Częstochowa, POLAND

    Robert Nowicki & Agata Pokropińska

  2. Department of Artificial InteligenceThe Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905r. 64, 90-222, Łódź, POLAND

    Robert Nowicki

Authors
  1. Robert Nowicki
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  2. Agata Pokropińska
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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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Nowicki, R., Pokropińska, A. (2004). Information Criterions Applied to Neuro-Fuzzy Architectures Design. 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_47

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_47

  • 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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