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Harmonic current classification using hybrid FAM-RBF neural network

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dc.contributor.authorLeow S.Y.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorWong S.Y.en_US
dc.contributor.authorid57193235970en_US
dc.contributor.authorid24448864400en_US
dc.contributor.authorid55812054100en_US
dc.date.accessioned2023-05-29T08:14:07Z
dc.date.available2023-05-29T08:14:07Z
dc.date.issued2020
dc.description.abstractIn this paper, the type of customers of electricity in Malaysia is classified into the type of electricity consumers based on the harmonic current data. A hybrid of Fuzzy Adaptive Resonance Theory with Mapping Algorithm (Fuzzy ARTMAP) and Radial Basis Function (RBF) neural network is developed (namely FAM-RBF), and it is used to classify the harmonic current into types of consumers. The result of the proposed neural network is discussed, and compared with other neural networks in this paper. The comparison result shows that the proposed FAM-RBF obtained the best performance result and is a truthful neural network to be used in this application. Copyright � 2020 Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/ijeecs.v18.i3.pp1551-1558
dc.identifier.epage1558
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85079163757
dc.identifier.spage1551
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85079163757&doi=10.11591%2fijeecs.v18.i3.pp1551-1558&partnerID=40&md5=c798704577935ed4f99b287ac9ee6dbc
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25775
dc.identifier.volume18
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleIndonesian Journal of Electrical Engineering and Computer Science
dc.titleHarmonic current classification using hybrid FAM-RBF neural networken_US
dc.typeArticleen_US
dspace.entity.typePublication
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