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

页码：185 / 194

页数：10

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