The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems

Type-2 fuzzy reasoning relations are the type-2 fuzzy relations obtained from a group of type-2 fuzzy reasonings by using extended t-(co)norm, which are essential for implementing type-2 fuzzy logic systems. In this paper an algorithm is provided for constructing type-2 fuzzy reasoning relations of...

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Main Authors: Shan Zhao, Hongxing Li
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/459508
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spelling doaj-b88a8da037e64c83a829990e57233ccd2020-11-25T00:28:43ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/459508459508The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic SystemsShan Zhao0Hongxing Li1School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, ChinaSchool of Control Science and Engineering, Dalian University of Technology, Dalian 116024, ChinaType-2 fuzzy reasoning relations are the type-2 fuzzy relations obtained from a group of type-2 fuzzy reasonings by using extended t-(co)norm, which are essential for implementing type-2 fuzzy logic systems. In this paper an algorithm is provided for constructing type-2 fuzzy reasoning relations of SISO type-2 fuzzy logic systems. First, we give some properties of extended t-(co)norm and simplify the expression of type-2 fuzzy reasoning relations in accordance with different input subdomains under certain conditions. And then different techniques are discussed to solve the simplified expressions on the input subdomains by using the related methods on solving fuzzy relation equations. Besides, it is pointed out that the computation amount level of the proposed algorithm is the same as that of polynomials and the possibility of applying the proposed algorithm in the construction of type-2 fuzzy reasoning relations is illustrated on several examples. Finally, the calculation of an arbitrary extended continuous t-norm can be obtained as the special case of the proposed algorithm.http://dx.doi.org/10.1155/2014/459508
collection DOAJ
language English
format Article
sources DOAJ
author Shan Zhao
Hongxing Li
spellingShingle Shan Zhao
Hongxing Li
The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
Journal of Applied Mathematics
author_facet Shan Zhao
Hongxing Li
author_sort Shan Zhao
title The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
title_short The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
title_full The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
title_fullStr The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
title_full_unstemmed The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems
title_sort construction of type-2 fuzzy reasoning relations for type-2 fuzzy logic systems
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2014-01-01
description Type-2 fuzzy reasoning relations are the type-2 fuzzy relations obtained from a group of type-2 fuzzy reasonings by using extended t-(co)norm, which are essential for implementing type-2 fuzzy logic systems. In this paper an algorithm is provided for constructing type-2 fuzzy reasoning relations of SISO type-2 fuzzy logic systems. First, we give some properties of extended t-(co)norm and simplify the expression of type-2 fuzzy reasoning relations in accordance with different input subdomains under certain conditions. And then different techniques are discussed to solve the simplified expressions on the input subdomains by using the related methods on solving fuzzy relation equations. Besides, it is pointed out that the computation amount level of the proposed algorithm is the same as that of polynomials and the possibility of applying the proposed algorithm in the construction of type-2 fuzzy reasoning relations is illustrated on several examples. Finally, the calculation of an arbitrary extended continuous t-norm can be obtained as the special case of the proposed algorithm.
url http://dx.doi.org/10.1155/2014/459508
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