Study on enhanced Karnik-Mendel algorithms: Initialization explanations and computation improvements

被引:58
作者
Liu, Xinwang [1 ,2 ]
Mendel, Jerry M. [2 ]
Wu, Dongrui [2 ,3 ]
机构
[1] Southeast Univ, Sch Econ & Management, Nanjing 210096, Jiangsu, Peoples R China
[2] Univ So Calif, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90089 USA
[3] GE Global Res, Ind Artificial Intelligence Lab, Niskayuna, NY 12309 USA
基金
中国国家自然科学基金;
关键词
Enhanced Karnik-Mendel (EKM) algorithms; Weighted EKM (WEKM) algorithms; Interval type-2 fuzzy set (IT2 FS); Numerical integration; Centroid computation; TYPE-2; FUZZY-LOGIC; WEIGHTED AVERAGE; UNCERTAINTY MEASURES; SETS;
D O I
10.1016/j.ins.2011.07.042
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Computing the centroid of an interval type-2 fuzzy set is an important operation in a type-2 fuzzy logic system, and is usually implemented by Karnik-Mendel (KM) iterative algorithms. By connecting KM algorithms and continuous KM algorithms together, this paper gives theoretical explanations on the initialization methods of KM and Enhanced Karnik-Mendel (EKM) algorithms, proposes exact methods for centroid computation of an interval type-2 fuzzy set, and extends the Enhanced Karnik-Mendel (EKM) algorithms to three different forms of weighted EKM (WEKM) algorithms. It shows that EKM algorithms become a special case of the WEKM algorithms when the weights of the latter are constant value. It also shows that, in general, the weighted EKM algorithms have smaller absolute error and faster convergence speed than the EKM algorithms which make them very attractive for real-time applications of fuzzy logic system. Four numerical examples are used to illustrate and analyze the performance of WEKM algorithms. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:75 / 91
页数:17
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