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- W4247663164 abstract "In this paper, for minimizing the cost from the ocean generator power production by optimizing the operation and maintenance (O&M) policy over an infinite time horizon, while considering the uncertainty of the renewable sources and components failure behaviors, we develop a self-healing framework for ocean energy systems. It consists of three major modules: data manipulation, health assessment, and decision-making. Specifically, a graph-theoretic approach is first proposed for ocean generator health monitoring utilizing multivariate time-series data, then, reinforcement learning (RL) based technique exploits the health states of the system that provides decision support for optimal O&M management.<br>" @default.
- W4247663164 created "2022-05-12" @default.
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- W4247663164 date "2020-07-30" @default.
- W4247663164 modified "2023-10-18" @default.
- W4247663164 title "Prognostic and Health Management in Ocean Energy System A Self-Healing Framework based on Reinforcement Learning" @default.
- W4247663164 doi "https://doi.org/10.36227/techrxiv.12733160" @default.
- W4247663164 hasPublicationYear "2020" @default.
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