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A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network

Automatic classification of Power Quality Disturbances (PQDs) is a challenging concern for both the utility and industry. In this paper, a novel technique of automatic classification of single and hybrid PQDs is proposed. The proposed algorithm consists of the Discrete Wavelet Transform (DWT) and Pr...

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主要な著者:	Khokhar, Suhail, Mohd. Zin, Abdullah Asuhaimi, Momen, Aslam Pervez, Mokhtar, Ahmad Safawi
フォーマット:	論文
出版事項:	Elsevier 2017
主題:	TK Electrical engineering. Electronics Nuclear engineering
オンライン･アクセス:	http://eprints.utm.my/id/eprint/66455/ http://dx.doi.org/10.1016/j.measurement.2016.10.013
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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