The α-weighted averaging operator

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F23%3A73619768" target="_blank" >RIV/61989592:15210/23:73619768 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0165011423003226" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0165011423003226</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.fss.2023.108677" target="_blank" >10.1016/j.fss.2023.108677</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The α-weighted averaging operator

Popis výsledku v původním jazyce

This paper introduces a new type of mean applicable in various areas of science and practice: the α-weighted averaging operator (AWA). AWA has all the properties required from a linear averaging operator and some additional ones. We discuss the applications of AWA in data aggregation in various areas including uncertainty modeling (summarization, defuzzification), multiple-criteria and multi-expert decision-making and evaluation. We prove that when applied to fuzzy numbers, the α-weighted average converges to the possibilistic mean of a fuzzy number with the increasing number of elements in its support. As such the α-weighted average is a more general aggregation operator than the original possibilistic mean. When fuzzy subsets of the real line represent the information to be aggregated, AWA provides new means for their defuzzification compatible with the possibilistic moments, but applicable to discrete and subnormal fuzzy sets. We also introduce a generalized formulation of the α-weighted averaging operator (GAWA) that can be applied in multiple-criteria and multi-expert evaluation and decision-making problems. We suggest the use of GAWA in operations research theory and applications in the context of data aggregation, multiple-criteria and group evaluation and decision-making.

Název v anglickém jazyce

The α-weighted averaging operator

Popis výsledku anglicky

This paper introduces a new type of mean applicable in various areas of science and practice: the α-weighted averaging operator (AWA). AWA has all the properties required from a linear averaging operator and some additional ones. We discuss the applications of AWA in data aggregation in various areas including uncertainty modeling (summarization, defuzzification), multiple-criteria and multi-expert decision-making and evaluation. We prove that when applied to fuzzy numbers, the α-weighted average converges to the possibilistic mean of a fuzzy number with the increasing number of elements in its support. As such the α-weighted average is a more general aggregation operator than the original possibilistic mean. When fuzzy subsets of the real line represent the information to be aggregated, AWA provides new means for their defuzzification compatible with the possibilistic moments, but applicable to discrete and subnormal fuzzy sets. We also introduce a generalized formulation of the α-weighted averaging operator (GAWA) that can be applied in multiple-criteria and multi-expert evaluation and decision-making problems. We suggest the use of GAWA in operations research theory and applications in the context of data aggregation, multiple-criteria and group evaluation and decision-making.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

FUZZY SETS AND SYSTEMS

ISSN

0165-0114

e-ISSN

1872-6801

Svazek periodika

471

Číslo periodika v rámci svazku

15 November 2023

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

1-12

Kód UT WoS článku

001069404200001

EID výsledku v databázi Scopus

2-s2.0-85172452145