PEDI-GAN: power equipment data imputation based on generative adversarial networks with auxiliary encoder
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-024-05891-7.pdf
Reference48 articles.
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3. Song H, Szafir DA (2019) Where’s my data? Evaluating visualizations with missing data. IEEE Trans Visual Comput Graphics 25(1):914–924. https://doi.org/10.1109/TVCG.2018.2864914
4. Tu C, He X, Shuai Z, Jiang F (2017) Big data issues in smart grid—a review. Renew Sustain Energy Rev 79:1099–1107. https://doi.org/10.1016/j.rser.2017.05.134
5. Wang Y, Yan J, Yang Z, Zhao Y, Liu T (2021) Optimizing GIS partial discharge pattern recognition in the ubiquitous power internet of things context: a mixnet deep learning model. Int J Electr Power Energy Syst. https://doi.org/10.1016/j.ijepes.2020.106484
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