Linear Discriminate Analysis And K-Nearest Neighbor Based Diagnostic Analytic Of Harmonic Source Identification

Jopri, Mohd Hatta and Abdullah, Abdul Rahim and Manap, Mustafa and Nor Shah, Mohd Badril and Sutikno, Tole and Too, Jing Wei (2021) Linear Discriminate Analysis And K-Nearest Neighbor Based Diagnostic Analytic Of Harmonic Source Identification. Bulletin of Electrical Engineering and Informatics, 10 (1). pp. 171-178. ISSN 2302-9285

Text LINEAR DISCRIMINATE ANALYSIS AND K-NEAREST NEIGHBOR BASED DIAGNOSIS ANALYTIC OF HARMONIC SOURCE IDENTIFICATION.PDF Download (465kB)

Abstract

The diagnostic analytic of harmonic source is crucial research due to identify and diagnose the harmonic source in the power system. This paper presents a comparison of machine learning (ML) algorithm known as linear discriminate analysis (LDA) and k-nearest neighbor (KNN) in identifying and diagnosing the harmonic sources. Voltage and current features that estimated from time-frequency representation (TFR) of S-transform analys is are used as the input for ML. Several unique cases of harmonic source location are considered, whereas harmonic voltage (HV) and harmonic current (HC) source type-load are used in the diagnosing process. To identify the best ML, each ML algorithm is executed 10 times due to prevent any overfitting result and the performance criteria are measured consist of the accuracy, precision, geometric mean, specificity, sensitivity, and F-measure are calculated.

Item Type:	Article
Uncontrolled Keywords:	Harmonic current source, Harmonic voltage source, K-nearest neighbor, Linear discriminate analysis, S-transform
Divisions:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Sabariah Ismail
Date Deposited:	17 Mar 2022 16:51
Last Modified:	17 Mar 2022 16:51
URI:	http://eprints.utem.edu.my/id/eprint/25784
Statistic Details:	View Download Statistic

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