Classification of power quality disturbances in microgrids using a multi-level global convolutional neural network and SDTransformer approach.

In addition, as the number of layers increases, the accuracy of both modules shows an improvement trend, but the speed of improvement slows down with the increase in the number of layers, indicating that increasing the number of layers can effectively improve the model performance, but the effect has a decreasing trend.

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