Application of Slantlet Transform Based Support Vector Machine for Power Quality Detection and Classification

ISSN Print: 2327-588X
ISSN Online: 2327-5901
www.scirp.net/journal/jpee
E-mail: [email protected]

Citations

"Application of Slantlet Transform Based Support Vector Machine for Power Quality Detection and Classification"
written by Faridah Hanim M. Noh, Hajime Miyauchi, M. Faizal Yaakub,
published by Journal of Power and Energy Engineering, Vol.3 No.4, 2015

has been cited by the following article(s):

[1]	Islanding detection technique using Slantlet Transform and Ridgelet Probabilistic Neural Network in grid-connected photovoltaic system
	Applied Energy, 2018

[2]	Research of the Role of Think Tank in Power System Deregulation
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[3]	Performance of Modified S-Transform for Power Quality Disturbance Detection and Classification
	Telkomnika, 2017

[4]	基于复阻抗与支持向量机的电能质量扰动分类方法
	安徽大学学报：自然科学版, 2016

[5]	An Approach to Wheel Loader Bucket Raise Time Detection
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[6]	基于复阻抗与支持向量机的电能质量扰动分类方法 A new classification method of power quality disturbances based on complex impedance and SVM
	2016

[1]	Detection and Characterisation of Atypical Harmonic Patterns in Big Power Quality Data IET Generation, Transmission & Distribution, 2025 DOI:10.1049/gtd2.70062

[2]	Signal processing approaches for power quality disturbance classification: A comprehensive review Results in Engineering, 2025 DOI:10.1016/j.rineng.2025.104569

[3]	Islanding detection technique using Slantlet Transform and Ridgelet Probabilistic Neural Network in grid-connected photovoltaic system Applied Energy, 2018 DOI:10.1016/j.apenergy.2018.09.145

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