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On type-reduction of type-2 fuzzy sets: A review

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APPLIED SOFT COMPUTING
卷 27, 期 -, 页码 614-627

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ELSEVIER
DOI: 10.1016/j.asoc.2014.04.031

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General type-2 fuzzy sets; Interval type-2 fuzzy sets; Type-reduction; Defuzzification; Fuzzy logic systems; Fuzzy clustering and classification

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As an undetachable module of type-2 (T2) fuzzy computations and reasoning, type-reduction methods play an important role in various fuzzy disciplines including fuzzy logic systems and fuzzy clustering. Importance of type-reduction techniques lies in the fact that they are the main tools for collecting the entire inherent vagueness of the data. Therefore, type-reduction methods form the output of type-2 fuzzy sets (T2 FSs) as the representative of the entire uncertainty in a given space. Hence, their accuracy, precision, and performance speed is of much interest. This paper, presents a comprehensive review on various type-reduction and defuzzification strategies for general and interval type-2 fuzzy sets and systems. It is tried to analyze the existing approaches from different point of views accompanied by extensive comparisons on different features of type-reduction methods to facilitate further research studies by the fuzzy community. (C) 2014 Elsevier B.V. All rights reserved.

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