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Defuzzyfication in Interpretation of Comparator Networks

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 854))

Abstract

We present an extension to the methods and algorithms for approximation of similarity known as Networks of Comparators. By interpreting the output of the network in terms of discrete fuzzy set we make it possible to employ various defuzzyfication techniques for the purpose of establishing a unique value of the output of comparator network. We illustrate the advantages of this approach using two examples.

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Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Łukasz Sosnowski

  2. Institute of Informatics, The University of Warsaw, Banacha 2, 02-097, Warsaw, Poland

    Marcin Szczuka

Authors
  1. Łukasz Sosnowski
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  2. Marcin Szczuka
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Corresponding author

Correspondence to Łukasz Sosnowski .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Universidad de Granada, Granada, Spain

    David A. Pelta

  5. Universidad de Málaga, Málaga, Málaga, Spain

    Inma P. Cabrera

  6. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Sosnowski, Ł., Szczuka, M. (2018). Defuzzyfication in Interpretation of Comparator Networks. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-91476-3_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91475-6

  • Online ISBN: 978-3-319-91476-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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