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Possibility and Gradual Number Approaches to Ranking Methods for Random Fuzzy Intervals

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Advances in Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 299))

Abstract

This paper deals with methods for ranking fuzzy intervals in connection with probabilistic and interval orderings. According to the interpretation of a fuzzy interval, various such extensions can be laid bare. In this paper, we especially consider extensions of probabilistic orderings using possibilistic interpretations of fuzzy intervals, crisp substitutes thereof, and gradual numbers. This framework can encompass the comparison of fuzzy random variables: coupling one form of probabilistic comparison with one form of interval comparison induces a method for ranking random fuzzy intervals.

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Author information

Authors and Affiliations

  1. Université Mouloud Mammeri de Tizi-Ouzou, Algeria

    Farid Aiche

  2. IRIT, CNRS and Université de Toulouse, France

    Didier Dubois

Authors
  1. Farid Aiche
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  2. Didier Dubois
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. CNRS UMR 7606, DAPA, LIP6 8, Université Pierre et Marie Curie - Paris6, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute — IONA College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Aiche, F., Dubois, D. (2012). Possibility and Gradual Number Approaches to Ranking Methods for Random Fuzzy Intervals. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31718-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-31718-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31717-0

  • Online ISBN: 978-3-642-31718-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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