Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/732
Title: Ordered fuzzy ARTMAP
Authors: Dagher, Issam 
Georgiopoulos, M
Heileman, G.L
Bebis, G
Affiliations: Department of Computer Engineering 
Keywords: Pattern classification
Fuzzy neural nets
ART neural nets
Subjects: Computational complexity
Issue Date: 2002
Publisher: IEEE
Part of: IEEE World Congress on Computational Intelligence. IEEE International Joint Conference on Neural Networks Proceedings
Start page: 1717
End page: 1722
Conference: IEEE International Joint Conference on Neural Networks (4-9 May 1998 : Anchorage, AK, USA) 
Abstract: 
In this paper we introduce a procedure that identifies a fixed order of training pattern presentation for fuzzy ARTMAP. The resulting algorithm is named ordered fuzzy ARTMAP. Experimental results have demonstrated that ordered fuzzy ARTMAP achieves a network performance that is better than the average fuzzy ARTMAP network performance (averaged over a fixed number of random orders of pattern presentations), and occasionally better than the maximum fuzzy ARTMAP network performance (maximum over a fixed number of random orders of pattern presentations). What is also worth noting is that the computational complexity of the aforementioned procedure is only a small fraction of the computational complexity required to complete the training phase of fuzzy ARTMAP for a single order of pattern presentation.
URI: https://scholarhub.balamand.edu.lb/handle/uob/732
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Computer Engineering

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