Transitions Between Fuzzified Aggregation Operators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F17%3A73583533" target="_blank" >RIV/61989592:15310/17:73583533 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989592:15810/17:73583533

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Transitions Between Fuzzified Aggregation Operators

Popis výsledku v původním jazyce

An important problem in the multiple-criteria decision-making is how to combine multiple evaluations according to the individual criteria into the overall evaluation. Many aggregation methods have been developed for this task. When the evaluations are expressed by fuzzy numbers, fuzzified versions of these methods can be used. There is usually a trade-off between the versatility of the aggregation operator and the number of its parameters that have to be set. Setting correct parameters can pose a problem for the decision-maker in case of a more complex aggregation method. This paper proposes to overcome the problem in the following way - instead of creating a complex model directly, a simpler model, which represents only a rough approximation, is used first. In the next step, the model is refined and the original simple aggregation method is replaced by a more complex one. The parameters for the new aggregation method are derived automatically. Two algorithms are presented in the paper for this task - the first one derives a FNV-fuzzy measure (fuzzy-number-valued fuzzy measure) for the fuzzified Choquet integral, the latter one proposes a fuzzy rule base for the fuzzy expert system.

Název v anglickém jazyce

Transitions Between Fuzzified Aggregation Operators

Popis výsledku anglicky

An important problem in the multiple-criteria decision-making is how to combine multiple evaluations according to the individual criteria into the overall evaluation. Many aggregation methods have been developed for this task. When the evaluations are expressed by fuzzy numbers, fuzzified versions of these methods can be used. There is usually a trade-off between the versatility of the aggregation operator and the number of its parameters that have to be set. Setting correct parameters can pose a problem for the decision-maker in case of a more complex aggregation method. This paper proposes to overcome the problem in the following way - instead of creating a complex model directly, a simpler model, which represents only a rough approximation, is used first. In the next step, the model is refined and the original simple aggregation method is replaced by a more complex one. The parameters for the new aggregation method are derived automatically. Two algorithms are presented in the paper for this task - the first one derives a FNV-fuzzy measure (fuzzy-number-valued fuzzy measure) for the fuzzified Choquet integral, the latter one proposes a fuzzy rule base for the fuzzy expert system.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA14-02424S" target="_blank" >GA14-02424S: Metody operačního výzkumu pro podporu rozhodování v podmínkách neurčitosti</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Journal of Multiple-Valued Logic and Soft Computing

ISSN

1542-3980

e-ISSN

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Svazek periodika

29

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

25

Strana od-do

505-529

Kód UT WoS článku

000415668000008

EID výsledku v databázi Scopus

2-s2.0-85034114077