Ship track prediction based on Bayesian optimization in temporal convolutional networks

Ship track prediction based on Bayesian optimization in temporal convolutional networks

ObjectiveAs the traditional ship trajectory prediction method is prone to gradient explosion and long calculation time, this paper seeks to improve its accuracy and calculation efficiency by proposing a ship trajectory prediction model based on an improved Bayesian optimization algorithm (IBOA) and...

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Bibliographic Details
Main Authors: Jinyuan LI, Faxin ZHU, Xianbin TENG, Qilin BI
Format: Article
Language:English
Published: Editorial Office of Chinese Journal of Ship Research 2024-12-01
Series:Zhongguo Jianchuan Yanjiu
Subjects:
navigation
neural networks
bayesian optimization algorithm
temporal convolutional networks
temporal pattern attention mechanism module
reversible residual networks
ais data
Online Access:http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03755
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http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03755

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