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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Institute of Advanced Engineering and Science,
2020-06-01.
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LEADER | 01965 am a22003133u 4500 | ||
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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 |