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What is Applsci 15 01442 V2 about?

This study presents a novel multi-scale deep learning algorithm using 1-D convolutional neural networks (CNNs) with attention mechanisms for the automatic classification of power quality disturbances (PQDs), achieving an accuracy of up to 99.49%. The approach addresses the limitations of traditional methods by directly learning complex patterns from PQ signals and utilizing an open-source dataset generator to create large-scale labeled datasets. The findings indicate significant improvements in the accuracy

Author

fayezeh.mahmoudnezhad

Language

EN