Study on Non-iterative Algorithms for Center-of-Sets Type-Reduction of Interval Type-2 Takagi–Sugeno–Kang Fuzzy Logic Systems

In the application of interval type-2 (IT2) Takagi–Sugeno–Kang (TSK) fuzzy logic systems (FLSs), the center-of-sets (COS) type-reduction (TR) is more advantageous than the centroid TR. This paper proposes three types of discrete non-iterative algorithms to solve the problem of COS TR in IT2 TSK FLSs...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of fuzzy systems Vol. 26; no. 8; pp. 2675 - 2687
Main Authors Zhou, Junge, Chen, Yang
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2024
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Centroids
Computational Intelligence
Engineering
Fuzzy logic
Fuzzy sets
Fuzzy systems
Iterative algorithms
Management Science
Operations Research
Simulation
Interval type-2 fuzzy logic systems
Non-iterative algorithms
Computational efficiency
Center-of-sets type-reduction
KM algorithms
Online AccessGet full text
ISSN1562-2479
2199-3211
DOI10.1007/s40815-024-01873-2

Cover

More Information
Summary:In the application of interval type-2 (IT2) Takagi–Sugeno–Kang (TSK) fuzzy logic systems (FLSs), the center-of-sets (COS) type-reduction (TR) is more advantageous than the centroid TR. This paper proposes three types of discrete non-iterative algorithms to solve the problem of COS TR in IT2 TSK FLSs. Multiple simulation experiments are carried out for the IT2 TSK FLSs with different fuzzy rule numbers. Experimental results show that the computational efficiencies of the three discrete non-iterative algorithms are better than that of Karnik–Mendel (KM) algorithms, which provides latent value for the application of type-2 FLSs.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1562-2479
2199-3211
DOI:10.1007/s40815-024-01873-2