Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning

Research article (IET Renewable Power Generation, 2022) · cited 21× · AI/ML
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Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning

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Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimal-control-strategy-for-solid-oxide-fuel-cellbased-hybrid-energy-system-using-deep-reinforcement-learning
MLA “Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimal-control-strategy-for-solid-oxide-fuel-cellbased-hybrid-energy-system-using-deep-reinforcement-learning.
BibTeX @misc{4ortxyz_optimal-control-strategy-for-solid-oxide-fuel-cellbased-hybrid-energy-system-using-deep-reinforcement-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning}}, year = {2026}, url = {https://4ort.xyz/entity/optimal-control-strategy-for-solid-oxide-fuel-cellbased-hybrid-energy-system-using-deep-reinforcement-learning}, note = {Accessed: 2026-05-24}}
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