An End-to-End Deep Learning Method for Voltage Sag Classification
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- Khokhar, Suhail & Mohd Zin, Abdullah Asuhaimi B. & Mokhtar, Ahmad Safawi B. & Pesaran, Mahmoud, 2015. "A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1650-1663.
- Wang, Shouxiang & Chen, Haiwen, 2019. "A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network," Applied Energy, Elsevier, vol. 235(C), pages 1126-1140.
- Haoyuan Sha & Fei Mei & Chenyu Zhang & Yi Pan & Jianyong Zheng, 2019. "Identification Method for Voltage Sags Based on K-means-Singular Value Decomposition and Least Squares Support Vector Machine," Energies, MDPI, vol. 12(6), pages 1-15, March.
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- Yunus Yalman & Tayfun Uyanık & Adnan Tan & Kamil Çağatay Bayındır & Yacine Terriche & Chun-Lien Su & Josep M. Guerrero, 2022. "Implementation of Voltage Sag Relative Location and Fault Type Identification Algorithm Using Real-Time Distribution System Data," Mathematics, MDPI, vol. 10(19), pages 1-13, September.
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Keywords
power quality; classification; neural networks; voltage sag; dataset;All these keywords.
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