On KM Algorithms for Solving Type-2 Fuzzy Set Problems

被引：153

作者：

Mendel, Jerry M. ^{[1
]}

机构：

[1] Univ So Calif, Inst Signal & Image Proc, Los Angeles, CA 90089 USA

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2013年 / 21卷 / 03期

关键词：

Centroid; general type-2 fuzzy sets (GT2 FSs); interval type-2 fuzzy sets (IT2 FSs); Karnik-Mendel (KM) algorithms; tutorial; type-reduction (TR); KARNIK-MENDEL ALGORITHMS; ALPHA-PLANE REPRESENTATION; CENTROID-FLOW ALGORITHM; LOGIC SYSTEMS; REASONABLE PROPERTIES; UNCERTAINTY MEASURES; WEIGHTED AVERAGE; REDUCTION; DEFUZZIFICATION; FUZZISTICS;

D O I：

10.1109/TFUZZ.2012.2227488

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Computing the centroid and performing type-reduction for type-2 fuzzy sets and systems are operations that must be taken into consideration. Karnik-Mendel (KM) algorithms are the standard ways to do these operations; however, because these algorithms are iterative, much research has been conducted during the past decade about centroid and type-reduction computations. This tutorial paper focuses on the research that has been conducted to 1) improve the KM algorithms; 2) understand the KM algorithms, leading to further improved algorithms; 3) eliminate the need for KM algorithms; 4) use the KM algorithms to solve other (nonfuzzy logic system) problems; and 5) use (or not use) KM algorithms for general type-2 fuzzy sets and fuzzy logic systems.

引用

页码：426 / 446

页数：21

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