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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy

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dc.citedby2
dc.contributor.authorLeow S.Y.en_US
dc.contributor.authorWong S.Y.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorYap H.J.en_US
dc.contributor.authorid57193235970en_US
dc.contributor.authorid55812054100en_US
dc.contributor.authorid24448864400en_US
dc.contributor.authorid35319362200en_US
dc.date.accessioned2023-05-29T06:39:26Z
dc.date.available2023-05-29T06:39:26Z
dc.date.issued2017
dc.descriptionE-learning; Functions; Fuzzy inference; Radial basis function networks; Fuzzy ARTMAP; Online learning; pruning; Radial basis functions; regression; Learning algorithmsen_US
dc.description.abstractIn this paper, a new online learning algorithm is proposed to learn a data sample in hybrid mode. This new algorithm is developed and referred as Growing and Pruning - Fuzzy ARTMAP-radial basis function (GAP-FAM-RBF) neural network. In this algorithm, fuzzy ARTMAP (FAM) network learns from training samples and radial basis function (RBF) network provides viable solutions. The GAP-FAM-RBF that proposed is able to learn online from the first data samples. The insignificant hidden neurons will be pruned. The performance of this algorithm is evaluated on regression applications. � 2016 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7813294
dc.identifier.doi10.1109/ICSGRC.2016.7813294
dc.identifier.epage21
dc.identifier.scopus2-s2.0-85011982314
dc.identifier.spage17
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85011982314&doi=10.1109%2fICSGRC.2016.7813294&partnerID=40&md5=38c1bcd8d1a901a5d83f6fa6194c3b38
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23318
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2016 7th IEEE Control and System Graduate Research Colloquium, ICSGRC 2016 - Proceeding
dc.titleA new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategyen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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