The Prediction and Dynamic Correction of Drifting Trajectory for Unmanned Maritime Equipment Based on Fully Connected Neural Network (FCNN) Embedding Model

At present, unmanned maritime equipment has become the main force in the implementation of marine exploration tasks. However, due to the complexity of the marine environment, equipment is susceptible to damage and loss. This is why achieving more effective search and rescue (SAR) of unmanned maritim...

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Autors principals:	Yuxuan Song, Dezhi Wang, Xiaodan Xiong, Xinghua Cheng, Lingzhi Huang, Yichao Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-12-01
Col·lecció:	Journal of Marine Science and Engineering
Matèries:	search and rescue unmanned maritime equipment drifting trajectory predictions fully connected neural network dynamic correction
Accés en línia:	https://www.mdpi.com/2077-1312/12/12/2262
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