Evaluating the significance of samples in deep learning-based transient stability assessment
Deep learning-based transient stability assessment has achieved big success in power system analyses. However, it is still unclear how much of the data is superfluous and which samples are important for training. In this work, we introduce the latest technique from the artificial intelligence commun...
Main Authors: | Le Zheng, Zheng Wang, Gengyin Li, Yanhui Xu |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-08-01
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Series: | Frontiers in Energy Research |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.925126/full |
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