Optimization Method of Underwater Flapping Foil Propulsion Performance Based on Gaussian Process Regression and Deep Reinforcement Learning

In order to overcome the complexity and variability of underwater working environments, as well as the difficulty of controlling the flapping motion due to the significant nonlinear characteristics and numerous variables involved, a direct exploration approach is proposed to search for the optimal f...

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Κύριος συγγραφέας:	YANG Yinghe, WEI Handi, FAN Dixia, LI Ang
Μορφή:	Artigo
Γλώσσα:	Chinês
Έκδοση:	Editorial Office of Journal of Shanghai Jiao Tong University 2025-01-01
Σειρά:	Shanghai Jiaotong Daxue xuebao
Θέματα:	underwater flapping foil gaussian process regression (gpr) deep reinforcement learning (drl) propulsion performance optimization
Διαθέσιμο Online:	https://xuebao.sjtu.edu.cn/article/2025/1006-2467/1006-2467-59-1-70.shtml
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