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Article type: Research Article
Authors: Chen, Yang; * | Yang, Jiaxiu
Affiliations: College of Science, Liaoning University of Technology, Jinzhou, China
Correspondence: [*] Corresponding author. Yang Chen, College of Science, Liaoning University of Technology, Jinzhou, 121001, China. E-mail: lxychenyang@lnut.edu.cn.
Abstract: In recent years, interval type-2 fuzzy logic systems (IT2 FLSs) have become a hot topic for the capability of coping with uncertainties. Compared with the centroid type-reduction (TR), investigating the center-of-sets (COS) TR of IT2 FLSs is more favorable for applying IT2 FLSs. Actually, it is still an open question for comparing Karnik-Mendel (KM) types of algorithms and other types of alternative algorithms for COS TR. This paper gives the block of fuzzy reasoning, COS TR, and defuzzification of IT2 FLSs based on Nagar-Bardini (NB), Nie-Tan (NT) and Begian-Melek-Mendel (BMM) noniterative algorithms. Six simulation experiments are used to show the performances of three types of noniterative algorithms. The proposed noniterative algorithms can obtain much higher computational efficiencies compared with the KM algorithms, which give the potential value for designing T2 FLSs.
Keywords: Interval type-2 fuzzy logic systems, center-of-sets type-reduction, Nagar-Bardini algorithms, computational efficiency, Nie-Tan algorithms
DOI: 10.3233/JIFS-202264
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11099-11106, 2021
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