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Fuzzy Linguistic Labels in Multi-expert Decision Making

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Theory and Practice of Natural Computing (TPNC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10687))

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Abstract

This paper presents an approach to modeling multi-expert decision systems. The proposed method is based on the idea of fuzzy linguistic label, which is suitable for analyzing real life decision-making process under uncertainty, where subjective criteria play an important role. A modified form of information system for modeling the action of a group of experts is introduced. The notions of dominating, boundary, and negative linguistic values are adopted. Furthermore, a novel definition of the fuzzy linguistic label, the measure of certainty of a linguistic label, and the compatibility function between elements of the universe and a linguistic label are given. Finally, a way of aggregating the experts’ knowledge for selecting a set of objects that best fit the preference of a decision-maker is proposed. Independent vectors of preference degrees for both the attributes and their linguistic values are applied. A simple illustrating example is provided, which presents an analysis of a decision process performed by three experts.

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Authors and Affiliations

  1. Department of Avionics and Control, Rzeszów University of Technology, Al. Powstańców Warszawy 8, 35-959, Rzeszów, Poland

    Alicja Mieszkowicz-Rolka & Leszek Rolka

Authors
  1. Alicja Mieszkowicz-Rolka
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  2. Leszek Rolka
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Correspondence to Leszek Rolka .

Editor information

Editors and Affiliations

  1. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  2. Academy of Sciences of the Czech Republic, Prague, Czech Republic

    Roman Neruda

  3. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

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Mieszkowicz-Rolka, A., Rolka, L. (2017). Fuzzy Linguistic Labels in Multi-expert Decision Making. In: Martín-Vide, C., Neruda, R., Vega-Rodríguez, M. (eds) Theory and Practice of Natural Computing. TPNC 2017. Lecture Notes in Computer Science(), vol 10687. Springer, Cham. https://doi.org/10.1007/978-3-319-71069-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-71069-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71068-6

  • Online ISBN: 978-3-319-71069-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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