Paper Info
Title
An Efficient High-Order Alpha-Plane Aggregation In General Type-2 Fuzzy Systems Using Newton-Cotes Rules
Abstract
Nowadays, general type-2 fuzzy systems are an attractive alternative for non-linear control problems because they provide good robustness in real-world environments, where there exist many noise sources. This kind of fuzzy systems can have better performance in comparison to type-1 fuzzy systems as they offer uncertainty handling capabilities. However, one of the main problems in implementing general type-2 fuzzy systems is their elevated computational cost. The computational cost of a general type-2 fuzzy system depends on the representation that is used, for example, the alpha-planes representation consists on a discretization of general type-2 fuzzy systems into several horizontal slices called alpha-planes, then solving every alpha-plane as an interval type-2 fuzzy system and after that the integration of the results to approximate a general type-2 fuzzy system. The main contribution of this work is the proposed computational cost reduction of the alpha-planes representation by optimizing the alpha-planes integration process based on the composite Newton-Cotes rules. In this way, the number of alpha-planes required for a good approximation is reduced, and the computational cost is also reduced by introducing new equations for the alpha-planes aggregation. Finally, a systematic comparative analysis of the improvement offered by the proposed method with respect to the conventional approach is presented.
Year
DOI
Venue
2021
10.1007/s40815-020-01031-4
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
Keywords
DocType
Volume
General type-2 fuzzy systems, Diagnosis systems, Uncertainty
Journal
23
Issue
ISSN
Citations 
4
1562-2479
1
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Emanuel Ontiveros-Robles110.34
Patricia Melin24009259.43
Oscar Castillo35289452.83