Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems

Interval type-2 fuzzy logic systems (IT2 FLSs) have been widely used in many areas. Among which, type-reduction (TR) is an important block for theoretical study. Noniterative algorithms do not involve the complicated iteration process and obtain the system output directly. By discovering the inner r...

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Main Authors: Yang Chen, Jinxia Wu, Jie Lan
Format: Article
Language:English
Published: AIMS Press 2020-10-01
Series:AIMS Mathematics
Subjects:
Online Access:https://www.aimspress.com/article/10.3934/math.2020494/fulltext.html
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author Yang Chen
Jinxia Wu
Jie Lan
author_facet Yang Chen
Jinxia Wu
Jie Lan
author_sort Yang Chen
collection DOAJ
description Interval type-2 fuzzy logic systems (IT2 FLSs) have been widely used in many areas. Among which, type-reduction (TR) is an important block for theoretical study. Noniterative algorithms do not involve the complicated iteration process and obtain the system output directly. By discovering the inner relations between discrete and continuous noniterative algorithms, this paper proposes three types of weighted-based noniterative according to the Newton-Cotes quadrature formulas in numerical integration techniques. Moreover, the continuous noniterative algorithms are considered as the benchmarks for computing. Four simulation experiments are provided to illustrate the performances of weighted-based noniterative algorithms for computing the defuzzified values of IT2 FLSs. Compared with the original noniterative algorithms, the proposed weighted-based algorithms can obtain smaller absolute errors and faster convergence speeds under the same sampling rate, which afford the potential values for designing T2 FLSs.
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spelling doaj.art-6304d24e1f704cccaac269661c097df22022-12-21T23:39:13ZengAIMS PressAIMS Mathematics2473-69882020-10-01567719774510.3934/math.2020494Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systemsYang Chen0Jinxia Wu1Jie Lan2College of Science, Liaoning University of Technology, Jinzhou, Liaoning, 121001, P. R. ChinaCollege of Science, Liaoning University of Technology, Jinzhou, Liaoning, 121001, P. R. ChinaCollege of Science, Liaoning University of Technology, Jinzhou, Liaoning, 121001, P. R. ChinaInterval type-2 fuzzy logic systems (IT2 FLSs) have been widely used in many areas. Among which, type-reduction (TR) is an important block for theoretical study. Noniterative algorithms do not involve the complicated iteration process and obtain the system output directly. By discovering the inner relations between discrete and continuous noniterative algorithms, this paper proposes three types of weighted-based noniterative according to the Newton-Cotes quadrature formulas in numerical integration techniques. Moreover, the continuous noniterative algorithms are considered as the benchmarks for computing. Four simulation experiments are provided to illustrate the performances of weighted-based noniterative algorithms for computing the defuzzified values of IT2 FLSs. Compared with the original noniterative algorithms, the proposed weighted-based algorithms can obtain smaller absolute errors and faster convergence speeds under the same sampling rate, which afford the potential values for designing T2 FLSs.https://www.aimspress.com/article/10.3934/math.2020494/fulltext.htmltype-reductionweighted nagar-bardini algorithmsweighted nie-tan algorithmsweighted begian-melek-mendel algorithmsabsolute errors
spellingShingle Yang Chen
Jinxia Wu
Jie Lan
Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
AIMS Mathematics
type-reduction
weighted nagar-bardini algorithms
weighted nie-tan algorithms
weighted begian-melek-mendel algorithms
absolute errors
title Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
title_full Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
title_fullStr Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
title_full_unstemmed Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
title_short Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems
title_sort study on weighted based noniterative algorithms for centroid type reduction of interval type 2 fuzzy logic systems
topic type-reduction
weighted nagar-bardini algorithms
weighted nie-tan algorithms
weighted begian-melek-mendel algorithms
absolute errors
url https://www.aimspress.com/article/10.3934/math.2020494/fulltext.html
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AT jinxiawu studyonweightedbasednoniterativealgorithmsforcentroidtypereductionofintervaltype2fuzzylogicsystems
AT jielan studyonweightedbasednoniterativealgorithmsforcentroidtypereductionofintervaltype2fuzzylogicsystems