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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| Pengarang-pengarang Utama: | , , , |
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| Format: | Artikel |
| Diterbitkan: |
Elsevier
2017
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| Subjek-subjek: | |
| Capaian Atas Talian: | http://eprints.utm.my/66455/ http://eprints.utm.my/66455/ http://eprints.utm.my/66455/ |
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