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Autor:
Nhat-Quang Dang, Trong-Tai Ho, Tuyet-Doan Vo-Nguyen, Young-Woo Youn, Hyeon-Soo Choi, Yong-Hwa Kim
Publikováno v:
Energies, Vol 17, Iss 1, p 4 (2023)
Supervised contrastive learning (SCL) has recently emerged as an alternative to conventional machine learning and deep neural networks. In this study, we propose an SCL model with data augmentation techniques using phase-resolved partial discharge (P
Externí odkaz:
https://doaj.org/article/5a26e9dda7da48f2937404fdabff4c2c
