Melting Probability Measure With OWA Operator to Generate Fuzzy Measure: The Crescent Method
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Melting Probability Measure With OWA Operator to Generate Fuzzy Measure: The Crescent Method
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE T FUZZY SYST
ISSN
1063-6706
e-ISSN
1941-0034
Volume of the periodical
27
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
7
Pages from-to
1309-1316
UT code for WoS article
000470837100015
EID of the result in the Scopus database
2-s2.0-85055677279