On the centroid of a general type-2 fuzzy set with monotonically increasing second membership functions

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Xianliang Liu , Zhihuan Hu , Weidong Zhang
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引用次数: 0

Abstract

In a type-2 fuzzy logic system, the centroid computation of a general type-2 fuzzy set (T2 FS) is one of the most important type reduction methods. Nearly all of the existing algorithms are based on the α-plane representation or z-slice representation. Therefore, all of these algorithms can only approximately compute the centroid of a general T2 FS and cannot obtain the analytic expression of the centroid of a general T2 FS. The main objective of this study is to obtain the analytic expression of the centroid of a general T2 FS with monotonically increasing second membership functions based on a discrete universe of discourse. First, assuming that the second membership functions of a general T2 FS is linear and monotonically increasing, a method is proposed to compute its centroid. Second, an approach to calculate the centroid of a general T2 FS is also analyzed, if the second membership functions are only monotonically increasing. Finally, two numerical examples are given to demonstrate the calculation processes of the proposed method in this study. Notably, the proposed method can also be employed to obtain the analytic expression of the centroid of a general T2 FS with monotonically decreasing second membership functions.
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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