Contrastive adversarial domain adaptation for machine remaining useful life prediction

Contrastive adversarial domain adaptation for machine remaining useful life prediction

Enabling precise forecasting of the remaining useful life (RUL) for machines can reduce maintenance cost, increase availability, and prevent catastrophic consequences. Data-driven RUL prediction methods have already achieved acclaimed performance. However, they usually assume that the training and t...

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書目詳細資料
Main Authors:	Mohamed Ragab, Chen, Zhenghua, Wu, Min, Foo, Chuan Sheng, Kwoh, Chee Keong, Yan, Ruqiang, Li, Xiaoli
其他作者:	School of Computer Science and Engineering
格式:	Article
語言:	English
出版:	2022
主題:	Engineering::Computer science and engineering Domain Adaptation Deep Learning
在線閱讀:	https://hdl.handle.net/10356/157026
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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