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Distance-based linguistic approximation methods: graphical analysis and numerical experiments

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F17%3A73581328" target="_blank" >RIV/61989592:15210/17:73581328 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Distance-based linguistic approximation methods: graphical analysis and numerical experiments

  • Original language description

    Linguistic approximation (LA) as a tool for converting the outputs of mathematical models into linguistic terms or expressions is a crucial tool in linguistic fuzzy modelling. The success of the models depends significantly on the ability of the users of these models to understand well enough the outputs provided by the models. Linguistic approximation offers a natural language for conveying information. On the other hand it is still an approximation of the original results and as such, there is information distortion taking place. In this paper we study several distance-based linguistic approximation methods and analyse their performance in terms of LA for Mamdani-type outputs of mathematical models using a numerical experiment. We provide graphical summaries of the performance of these distance measures in LA as well as the frequencies of choosing specific linguistic labels considered to be the values of an extended linguistic scale. We discuss the differences in the focus of these methods and its implications for their usability. The paper strives to increase understanding of the LA methods and to contribute to the creation of a LA road map for practical use.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    35th International Conference Mathematical Methods in Economics MME 2017 Conference Proceedings

  • ISBN

    978-80-7435-678-0

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    6

  • Pages from-to

    777-782

  • Publisher name

    Gaudeamus

  • Place of publication

    Hradec Králové

  • Event location

    Hradec Králové

  • Event date

    Sep 13, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article