Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6905551 | Applied Soft Computing | 2015 | 14 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Abolfazl Doostparast Torshizi, Mohammad Hossein Fazel Zarandi, Hamzeh Zakeri,