FuzzME: A New Software for Multiple-Criteria Fuzzy Evaluation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F10%3A10224074" target="_blank" >RIV/61989592:15310/10:10224074 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

FuzzME: A New Software for Multiple-Criteria Fuzzy Evaluation

Popis výsledku v původním jazyce

This paper presents the software product FuzzME that was developed as a tool for creating fuzzy models of multiple-criteria evaluation and decision making. The type of evaluation employed in the fuzzy models fully agrees with the paradigm of the fuzzy set theory; the valuations express the (fuzzy) degrees of fulfillment of corresponding goals. In FuzzME, a goals tree is the basic structure of evaluation. Within the goals tree, the aggregation of partial fuzzy evaluations is done either by one of fuzzified aggregation perators or by a fuzzy expert system. The choice of the appropriate mode of aggregation depends on the relationships among evaluation criteria. FuzzME allows the utilization of following aggregation methods: fuzzy weighted average, fuzzy OWA operator, fuzzified WOWA operator, fuzzified Choquet integral, and fuzzy expert system. In this paper, all these methods will be described and the conditions for their use will be studied.

Název v anglickém jazyce

FuzzME: A New Software for Multiple-Criteria Fuzzy Evaluation

Popis výsledku anglicky

This paper presents the software product FuzzME that was developed as a tool for creating fuzzy models of multiple-criteria evaluation and decision making. The type of evaluation employed in the fuzzy models fully agrees with the paradigm of the fuzzy set theory; the valuations express the (fuzzy) degrees of fulfillment of corresponding goals. In FuzzME, a goals tree is the basic structure of evaluation. Within the goals tree, the aggregation of partial fuzzy evaluations is done either by one of fuzzified aggregation perators or by a fuzzy expert system. The choice of the appropriate mode of aggregation depends on the relationships among evaluation criteria. FuzzME allows the utilization of following aggregation methods: fuzzy weighted average, fuzzy OWA operator, fuzzified WOWA operator, fuzzified Choquet integral, and fuzzy expert system. In this paper, all these methods will be described and the conditions for their use will be studied.

Druh

O - Ostatní výsledky

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

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