期刊
INFORMATION SCIENCES
卷 179, 期 13, 页码 2102-2122出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2008.04.009
关键词
Fuzzy membership function generation; Interval type-2 fuzzy sets; Fuzzy C-means; Footprint of uncertainty
资金
- Defense Acquisition Program Administration and Agency for Defense Development, Korea [UD070007AD]
Type-2 fuzzy sets (T2 FSs) have been shown to manage uncertainty more effectively than T1 fuzzy sets (T1 FSs) in several areas of engineering [4,6-12,15-18,21-27,30]. However, computing with T2 FSs can require undesirably large amount of computations since it involves numerous embedded T2 FSs. To reduce the complexity, interval type-2 fuzzy sets (IT2 FSs) can be used, since the secondary memberships are all equal to one [21]. In this paper, three novel interval type-2 fuzzy membership function (IT2 FMF) generation methods are proposed. The methods are based on heuristics, histograms, and interval type-2 fuzzy C-means. The performance of the methods is evaluated by applying them to back-propagation neural networks (BPNNs). Experimental results for several data sets are given to show the effectiveness of the proposed membership assignments. (C) 2008 Elsevier Inc. All rights reserved.
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