CPU runtime and accuracy for each model.

<div><p>The large-scale integration of offshore wind power into the power grid has brought serious challenges to the power system power quality. Aiming at the problem of power quality disturbance detection and classification, this paper proposes a novel algorithm based on fast S-transfor...

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Bibliographic Details
Main Author:	Minan Tang (20389941) (author)
Other Authors:	Hongjie Wang (54357) (author), Jiandong Qiu (20389944) (author), Zhanglong Tao (20389947) (author), Tong Yang (103174) (author)
Published:	2024
Subjects:	Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified simulation experimental platform simulated disturbance signals perform simulation verification experimental results show crested porcupine optimizer convolutional neural network brought serious challenges offshore wind power offshore wind grid optimal classification performance novel algorithm based cnn classification model power grid model established established based optimized cnn cnn method classification accuracy xlink "> waveform characteristics scale integration intrinsic mechanism frequency diagrams feature selection feature extraction feature extracted cpo algorithm connected disturbances comparative analysis classifier achieves best hyperparameters accurately identify
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CPU runtime and accuracy for each model.

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