Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
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DOI: 10.1016/j.ress.2023.109496
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References listed on IDEAS
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Cited by:
- Kamariotis, Antonios & Tatsis, Konstantinos & Chatzi, Eleni & Goebel, Kai & Straub, Daniel, 2024. "A metric for assessing and optimizing data-driven prognostic algorithms for predictive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
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Keywords
Partially observable Markov decision processes; Bayesian inference; Optimal maintenance planning; Model uncertainty; Hidden Markov models; Dynamic Programming;All these keywords.
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