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Sequential Classification Via Fuzzy Relations

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Artificial Intelligence and Soft Computing – ICAISC 2006 (ICAISC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

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Abstract

In this paper there are developed and evaluated methods for performing sequential classification (SC) using fuzzy relations defined on product of class set and fuzzified feature space. First on the base of learning set, fuzzy relation in the proposed method is determined as a solution of appropriate optimization problem. Next, this relation in the form of matrix of membership degrees is used at successive instants of sequential decision process. Three various algorithms of SC which differ both in the sets of input data and procedure are described. Proposed algorithms were practically applied to the computer-aided recognition of patient’s acid-base equilibrium states where as an optimization procedure the real-coded genetic algorithm (RGA) was used.

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Author information

Authors and Affiliations

  1. Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski & Andrzej Zolnierek

Authors
  1. Marek Kurzynski
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  2. Andrzej Zolnierek
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Editor information

Editors and Affiliations

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

    Leszek Rutkowski

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

    Ryszard Tadeusiewicz

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

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Kurzynski, M., Zolnierek, A. (2006). Sequential Classification Via Fuzzy Relations. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_65

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  • DOI: https://doi.org/10.1007/11785231_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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