Interval Type-2 Fuzzy Possibilistic C-Means Clustering Algorithm

被引：8
|
作者：
Rubio, E. [1 ]
Castillo, Oscar [1 ]
Melin, Patricia [1 ]
机构：
[1] Tijuana Inst Technol, Div Grad Studies & Res, Tijuana, Mexico
来源：
RECENT DEVELOPMENTS AND NEW DIRECTION IN SOFT-COMPUTING FOUNDATIONS AND APPLICATIONS | 2016年 / 342卷
关键词：
Fuzzy sets; Fuzzy C-means; Possibilistic C-means; Interval type-2 clustering algorithm; TISSUE DIFFERENTIATION; CLASSIFICATION;
D O I：
10.1007/978-3-319-32229-2_14
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present the extension of the fuzzy possibilistic C-means (FPCM) algorithm using type-2 fuzzy logic techniques, with the goal of improving the performance of this algorithm. We also performed the comparison of this proposed algorithm against the interval type-2 fuzzy C-means (IT2FCM) algorithm to observe whether the proposed approach performs better than this algorithm. The proposed extension was realized considering both of the weight exponents (fuzzy and possibilistic), m and eta, as interval fuzzy sets.
引用
收藏
页码：185 / 194
页数：10
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