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Statements

Subject Item
n2:RIV%2F61988987%3A17610%2F13%3AA1400ZO0%21RIV14-MSM-17610___
rdf:type
n14:Vysledek skos:Concept
dcterms:description
We consider the prototypical case of an increasing relationship between each of the input variables and the output variable. When using fuzzy rule-based models, this desired monotonicity is reflected in the rule base, given an appropriate ordering on the fuzzy sets involved in the respective input and output domains. However, fuzzy rule-based modelling involves a final defuzzification step, possibly resulting in a function that is no longer monotone. In the context of Mamdani--Assilian conjunctive fuzzy models, ample attention has been paid to this problem, both for the center-of-gravity defuzzification and mean-of-maxima defuzzification methods. In this paper, we show that for implicative fuzzy models, the non-monotonicity problem can be circumvented by making explicit the semantics of the fuzzy rules by subjecting the antecedent and consequent fuzzy sets to the at-least and/or at-most modifiers. We consider the prototypical case of an increasing relationship between each of the input variables and the output variable. When using fuzzy rule-based models, this desired monotonicity is reflected in the rule base, given an appropriate ordering on the fuzzy sets involved in the respective input and output domains. However, fuzzy rule-based modelling involves a final defuzzification step, possibly resulting in a function that is no longer monotone. In the context of Mamdani--Assilian conjunctive fuzzy models, ample attention has been paid to this problem, both for the center-of-gravity defuzzification and mean-of-maxima defuzzification methods. In this paper, we show that for implicative fuzzy models, the non-monotonicity problem can be circumvented by making explicit the semantics of the fuzzy rules by subjecting the antecedent and consequent fuzzy sets to the at-least and/or at-most modifiers.
dcterms:title
Implication-based models of monotone fuzzy rule bases Implication-based models of monotone fuzzy rule bases
skos:prefLabel
Implication-based models of monotone fuzzy rule bases Implication-based models of monotone fuzzy rule bases
skos:notation
RIV/61988987:17610/13:A1400ZO0!RIV14-MSM-17610___
n14:predkladatel
n15:orjk%3A17610
n7:aktivita
n11:O
n7:aktivity
O
n7:cisloPeriodika
1
n7:dodaniDat
n8:2014
n7:domaciTvurceVysledku
n17:6800327
n7:druhVysledku
n13:J
n7:duvernostUdaju
n18:S
n7:entitaPredkladatele
n16:predkladatel
n7:idSjednocenehoVysledku
79209
n7:idVysledku
RIV/61988987:17610/13:A1400ZO0
n7:jazykVysledku
n12:eng
n7:klicovaSlova
Fuzzy rule-based models; Implicative models; Defuzzification; Monotonicity; At least and at most modifiers
n7:klicoveSlovo
n10:Monotonicity n10:Fuzzy%20rule-based%20models n10:At%20least%20and%20at%20most%20modifiers n10:Implicative%20models n10:Defuzzification
n7:kodStatuVydavatele
NL - Nizozemsko
n7:kontrolniKodProRIV
[153BF184AD0A]
n7:nazevZdroje
FUZZY SET SYST
n7:obor
n9:BA
n7:pocetDomacichTvurcuVysledku
1
n7:pocetTvurcuVysledku
2
n7:rokUplatneniVysledku
n8:2013
n7:svazekPeriodika
232
n7:tvurceVysledku
De Baets, Bernard Štěpnička, Martin
s:issn
0165-0114
s:numberOfPages
22
n5:organizacniJednotka
17610