On KM Algorithms for Solving Type-2 Fuzzy Set Problems

被引:146
|
作者
Mendel, Jerry M. [1 ]
机构
[1] Univ So Calif, Inst Signal & Image Proc, Los Angeles, CA 90089 USA
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
收藏
页码:426 / 446
页数:21
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