Melting Probability Measure With OWA Operator to Generate Fuzzy Measure: The Crescent Method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F19%3AA20020WA" target="_blank" >RIV/61988987:17610/19:A20020WA - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8502859" target="_blank" >https://ieeexplore.ieee.org/document/8502859</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TFUZZ.2018.2877605" target="_blank" >10.1109/TFUZZ.2018.2877605</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Melting Probability Measure With OWA Operator to Generate Fuzzy Measure: The Crescent Method

Popis výsledku v původním jazyce

Given probability information, i.e., a probability measure m with a random variable x on the outcome space N, the expected value of that random variable is commonly used as some valuable evaluation result for further decision making. However, there is no guarantee that the given probability information will he convincing to every decision maker. This is possible because decision makers may question the reliability of that provided probability information and can also be because decision makers often have their own different optimistic/pessimistic preferences. Often, such optimistic/pessimistic preferences can he easily embodied and expressed by some ordered weighted average (OWA) weight functions w. This study first compares and analyzes some simpler methods to melt the given OWA weight functions w with the given probability measure in to generate a new probability measure, pointing out their respective advantages and shortcomings. Then, this study proposes the melting axioms, which will both conform to our intuition and have mathematical reasonability. As the main finding of this study, we then propose the Crescent Method, which will effectively melt the given OWA weight function w with the given probability measure in to generate a final resulted fuzzy measure. Based on that melted fuzzy measure, we perform the Choquet integral of x as the more convincing evaluation result to decision makers with preference w. The study also proposes several interesting mathematical results such as the orness of resulted fuzzy measure will always be equal to the orness of the given OWA weight function w.

Název v anglickém jazyce

Melting Probability Measure With OWA Operator to Generate Fuzzy Measure: The Crescent Method

Popis výsledku anglicky

Given probability information, i.e., a probability measure m with a random variable x on the outcome space N, the expected value of that random variable is commonly used as some valuable evaluation result for further decision making. However, there is no guarantee that the given probability information will he convincing to every decision maker. This is possible because decision makers may question the reliability of that provided probability information and can also be because decision makers often have their own different optimistic/pessimistic preferences. Often, such optimistic/pessimistic preferences can he easily embodied and expressed by some ordered weighted average (OWA) weight functions w. This study first compares and analyzes some simpler methods to melt the given OWA weight functions w with the given probability measure in to generate a new probability measure, pointing out their respective advantages and shortcomings. Then, this study proposes the melting axioms, which will both conform to our intuition and have mathematical reasonability. As the main finding of this study, we then propose the Crescent Method, which will effectively melt the given OWA weight function w with the given probability measure in to generate a final resulted fuzzy measure. Based on that melted fuzzy measure, we perform the Choquet integral of x as the more convincing evaluation result to decision makers with preference w. The study also proposes several interesting mathematical results such as the orness of resulted fuzzy measure will always be equal to the orness of the given OWA weight function w.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

IEEE T FUZZY SYST

ISSN

1063-6706

e-ISSN

1941-0034

Svazek periodika

27

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

1309-1316

Kód UT WoS článku

000470837100015

EID výsledku v databázi Scopus

2-s2.0-85055677279