A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties
Autor(en): |
Jose Caceres
(Mechanical Engineering Department University of Chile Santiago Chile)
Danilo Gonzalez (Mechanical Engineering Department University of Chile Santiago Chile) Taotao Zhou (Center for Risk and Reliability University of Maryland College Park Maryland USA) Enrique Lopez Droguett (Department of Civil and Environmental Engineering, and B. John Garrick Institute for the Risk Sciences University of California Los Angeles Los Angeles California USA) |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Structural Control and Health Monitoring, Juni 2021, n. 10, v. 28 |
DOI: | 10.1002/stc.2811 |
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Datenseite - Reference-ID
10612479 - Veröffentlicht am:
09.07.2021 - Geändert am:
14.09.2021