Improving the Fuzzy Min-Max Neural Network with a K-nearest Hyperbox Expansion Rule for Pattern Classification

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Improving the Fuzzy Min-Max Neural Network with a K-nearest Hyperbox Expansion Rule for Pattern Classification

An improved Fuzzy Min-Max (FMM) neural network with a K-nearest hyperbox expansion rule is proposed in this paper. The aim is to reduce the FMM network complexity for undertaking pattern classification tasks. In the proposed model, a useful modification to overcome a number of identified limitations...

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Bibliographic Details
Main Authors:	Mohammed, Mohammed Falah, Chee, Peng Lim
Format:	Article
Language:	English
Published:	Elsevier Ltd 2017
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/16440/ http://umpir.ump.edu.my/id/eprint/16440/1/fskkp-2017-falah-Improving%20the%20fuzzy%20min-max1.pdf

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