A General Data-Driven Framework for Remaining Useful Life Estimation with Uncertainty Quantification Using Split Conformal Prediction
Author:
Affiliation:
1. Politecnico di Milano,Department of Energy,Milan,Italy
Funder
China Scholarship Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10380806/10380972/10381131.pdf?arnumber=10381131
Reference30 articles.
1. Prognostics and Remaining Useful Life Prediction of Machinery: Advances, Opportunities and Challenges
2. Prognostics and health management: A review from the perspectives of design, development and decision
3. Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice
4. A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties
5. Significance, interpretation, and quantification of uncertainty in prognostics and remaining useful life prediction
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