Interpolativity of at-least and at-most models of monotone single-input/single-output fuzzy rule bases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F13%3AA1300ZNZ" target="_blank" >RIV/61988987:17610/13:A1300ZNZ - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Interpolativity of at-least and at-most models of monotone single-input/single-output fuzzy rule bases

Popis výsledku v původním jazyce

Interpolativity is one of the most important properties of a fuzzy inference system. It is well known that normal antecedent fuzzy sets forming a Ruspini partition constitute a practical setting ensuring interpolativity. In case of a fuzzy rule base expressing a monotone relationship, another desirable property is the monotonicity of the resulting function (after defuzzification). Unfortunately, this goal may often only be reached through the application of the at-least and/or at-most modifiers to the antecedent and consequent fuzzy sets. However, this approach does not seem compatible with the practical setting of a Ruspini partition. This paper shows that the situation is less conflicting than it seems, and that interpolativity can still be guaranteed, in the same practical setting, and, interestingly, from two different modeling points of view. This paper addresses the case of single-input single-output fuzzy rules.

Název v anglickém jazyce

Interpolativity of at-least and at-most models of monotone single-input/single-output fuzzy rule bases

Popis výsledku anglicky

Interpolativity is one of the most important properties of a fuzzy inference system. It is well known that normal antecedent fuzzy sets forming a Ruspini partition constitute a practical setting ensuring interpolativity. In case of a fuzzy rule base expressing a monotone relationship, another desirable property is the monotonicity of the resulting function (after defuzzification). Unfortunately, this goal may often only be reached through the application of the at-least and/or at-most modifiers to the antecedent and consequent fuzzy sets. However, this approach does not seem compatible with the practical setting of a Ruspini partition. This paper shows that the situation is less conflicting than it seems, and that interpolativity can still be guaranteed, in the same practical setting, and, interestingly, from two different modeling points of view. This paper addresses the case of single-input single-output fuzzy rules.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

<a href="/cs/project/IAA108270902" target="_blank" >IAA108270902: Teorie semilineárních svazově uspořádaných prostorů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

INFORM SCIENCES

ISSN

0020-0255

e-ISSN

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Svazek periodika

234

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

16-28

Kód UT WoS článku

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EID výsledku v databázi Scopus

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