Sugeno-Like Operators in Preference and Uncertain Environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73621110" target="_blank" >RIV/61989592:15310/23:73621110 - isvavai.cz</a>

Výsledek na webu

<a href="https://obd.upol.cz/id_publ/333200997" target="_blank" >https://obd.upol.cz/id_publ/333200997</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TFUZZ.2022.3217369" target="_blank" >10.1109/TFUZZ.2022.3217369</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sugeno-Like Operators in Preference and Uncertain Environments

Popis výsledku v původním jazyce

Sugeno-like operators are binary operations-based generalization of Sugeno integral and are still defined on real valued fuzzy measures. This article discusses the aggregation methods in the situation where both inputs and fuzzy measures are attached with numerical uncertainties. That is, when an input vector and a fuzzy measure are given, each of the entries of the vector and the measure value on each subset can be attached with numerical uncertainty degrees. To fulfill this meaningful aim of performing Sugeno-like aggregation with numerical uncertainties, it needs two parts of work. We first formally define basic uncertain vector and basic uncertain fuzzy measure. Then, we discuss the methods to construct or adjust basic uncertain vector and basic uncertain fuzzy measure in two situations, the general fuzzy measure situation and the probability measure only situation, respectively. With uncertain input and uncertain fuzzy measure, we then accordingly propose the corresponding restricted Sugeno-like operator, for which some different logic restrictions are analyzed. All the proposals also have full consistency for they can immediately degenerates into Sugeno-like operator when the attached uncertainties disappear.

Název v anglickém jazyce

Sugeno-Like Operators in Preference and Uncertain Environments

Popis výsledku anglicky

Sugeno-like operators are binary operations-based generalization of Sugeno integral and are still defined on real valued fuzzy measures. This article discusses the aggregation methods in the situation where both inputs and fuzzy measures are attached with numerical uncertainties. That is, when an input vector and a fuzzy measure are given, each of the entries of the vector and the measure value on each subset can be attached with numerical uncertainty degrees. To fulfill this meaningful aim of performing Sugeno-like aggregation with numerical uncertainties, it needs two parts of work. We first formally define basic uncertain vector and basic uncertain fuzzy measure. Then, we discuss the methods to construct or adjust basic uncertain vector and basic uncertain fuzzy measure in two situations, the general fuzzy measure situation and the probability measure only situation, respectively. With uncertain input and uncertain fuzzy measure, we then accordingly propose the corresponding restricted Sugeno-like operator, for which some different logic restrictions are analyzed. All the proposals also have full consistency for they can immediately degenerates into Sugeno-like operator when the attached uncertainties disappear.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

IEEE TRANSACTIONS ON FUZZY SYSTEMS

ISSN

1063-6706

e-ISSN

1941-0034

Svazek periodika

31

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

2092-2098

Kód UT WoS článku

001001059800028

EID výsledku v databázi Scopus

2-s2.0-85141535993