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Harmonic current classification using hybrid FAM-RBF neural network

In 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 (name...

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Main Authors: Leow S.Y., Yap K.S., Wong S.Y.
Other Authors: 57193235970
Format: Article
Published: Institute of Advanced Engineering and Science 2023
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spelling my.uniten.dspace-257752023-05-29T16:14:08Z Harmonic current classification using hybrid FAM-RBF neural network Leow S.Y. Yap K.S. Wong S.Y. 57193235970 24448864400 55812054100 In 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. Final 2023-05-29T08:14:07Z 2023-05-29T08:14:07Z 2020 Article 10.11591/ijeecs.v18.i3.pp1551-1558 2-s2.0-85079163757 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079163757&doi=10.11591%2fijeecs.v18.i3.pp1551-1558&partnerID=40&md5=c798704577935ed4f99b287ac9ee6dbc https://irepository.uniten.edu.my/handle/123456789/25775 18 3 1551 1558 All Open Access, Gold, Green Institute of Advanced Engineering and Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description In 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.
author2 57193235970
author_facet 57193235970
Leow S.Y.
Yap K.S.
Wong S.Y.
format Article
author Leow S.Y.
Yap K.S.
Wong S.Y.
spellingShingle Leow S.Y.
Yap K.S.
Wong S.Y.
Harmonic current classification using hybrid FAM-RBF neural network
author_sort Leow S.Y.
title Harmonic current classification using hybrid FAM-RBF neural network
title_short Harmonic current classification using hybrid FAM-RBF neural network
title_full Harmonic current classification using hybrid FAM-RBF neural network
title_fullStr Harmonic current classification using hybrid FAM-RBF neural network
title_full_unstemmed Harmonic current classification using hybrid FAM-RBF neural network
title_sort harmonic current classification using hybrid fam-rbf neural network
publisher Institute of Advanced Engineering and Science
publishDate 2023
_version_ 1806423271706460160
score 13.211869

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