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A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties

Author(s): (Mechanical Engineering Department University of Chile Santiago Chile)
(Mechanical Engineering Department University of Chile Santiago Chile)
ORCID (Center for Risk and Reliability University of Maryland College Park Maryland USA)
(Department of Civil and Environmental Engineering, and B. John Garrick Institute for the Risk Sciences University of California Los Angeles Los Angeles California USA)
Medium: journal article
Language(s): English
Published in: Structural Control and Health Monitoring, , n. 10, v. 28
DOI: 10.1002/stc.2811
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1002/stc.2811.
  • About this
    data sheet
  • Reference-ID
    10612479
  • Published on:
    09/07/2021
  • Last updated on:
    14/09/2021
 
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