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Problems of Identification of Cloud-Based Fuzzy Evolving Systems

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Artificial Intelligence and Soft Computing (ICAISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9692))

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Abstract

In this paper some problems that arise in identification of nonlinear systems described by the cloud-based fuzzy rule-based model are shown. These models do not assume fixed partitioning of the space of antecedent variables. The Mahalanobis distance among the data samples is proposed for local density calculation which is more suitable when the data are scattered around the input-output surface. The identification algorithms are given in a recursive form which is necessary for the implementation of an evolving system. The proposed algorithms are illustrated on a simple simulation model of a static system.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000, Ljubljana, Slovenia

    Sašo Blažič & Igor Škrjanc

Authors
  1. Sašo Blažič
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  2. Igor Škrjanc
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Corresponding author

Correspondence to Sašo Blažič .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2016 Springer International Publishing Switzerland

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Blažič, S., Škrjanc, I. (2016). Problems of Identification of Cloud-Based Fuzzy Evolving Systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9692. Springer, Cham. https://doi.org/10.1007/978-3-319-39378-0_16

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  • DOI: https://doi.org/10.1007/978-3-319-39378-0_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39377-3

  • Online ISBN: 978-3-319-39378-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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