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, Shoun Ying (Author), Yap, Keem Siah (Author), Wong, Shen Yuong (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2020-06-01.
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LEADER 01965 am a22003133u 4500
001 ijeecs21130_13785
042 |a dc 
100 1 0 |a Leow, Shoun Ying  |e author 
100 1 0 |e contributor 
700 1 0 |a Yap, Keem Siah  |e author 
700 1 0 |a Wong, Shen Yuong  |e author 
245 0 0 |a Harmonic current classification using hybrid FAM-RBF neural network 
260 |b Institute of Advanced Engineering and Science,   |c 2020-06-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21130 
520 |a 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. 
540 |a Copyright (c) 2019 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690 |a Harmonic current; Electrical loads; Type of electricity consumers; Fuzzy ARTMAP; Radial basis function 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 18, No 3: June 2020; 1551-1558 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v18.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21130/13785 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21130/13785  |z Get fulltext