Harmonic current classification using hybrid FAM-RBF neural network

Shoun Ying Leow (Universiti Tenaga Nasional)
Keem Siah Yap (Universiti Tenaga Nasional)
Shen Yuong Wong (Xiamen University Malaysia)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 18, No 3: June 2020

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.