Research Article
Research on Load Feature Extraction Method of Typical Users Based on Deep Learning
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@INPROCEEDINGS{10.1007/978-3-030-82562-1_13, author={Zhu Lian-huan and Wei Wei and Zhu Wei-yang and Ding Can-song and Shen Kai and Fu Guan-hua}, title={Research on Load Feature Extraction Method of Typical Users Based on Deep Learning}, proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part I}, proceedings_a={ICMTEL}, year={2021}, month={7}, keywords={Deep learning Typical user Load feature Feature extraction}, doi={10.1007/978-3-030-82562-1_13} }- Zhu Lian-huan
Wei Wei
Zhu Wei-yang
Ding Can-song
Shen Kai
Fu Guan-hua
Year: 2021
Research on Load Feature Extraction Method of Typical Users Based on Deep Learning
ICMTEL
Springer
DOI: 10.1007/978-3-030-82562-1_13
Abstract
In order to improve the accuracy of typical user load feature extraction, this paper proposes a typical user load feature extraction method based on deep learning. Using k-means algorithm to cluster user load data, select typical user load sample data from the clustering results, and classify user load categories, and implement the extraction of typical user load features based on the classification results combined with deep learning methods. The experimental test results show that the method in this paper has high accuracy in the extraction of typical user load characteristics, high accuracy in load recognition, and good practical application effects.
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