Vessel trajectory prediction based on improved multi-output support vector

被引：0
|
作者：
Yang Z. [1 ]
Zhang Z. [1 ]
Shang X. [1 ]
Cao Z. [1 ]
Sun Z. [1 ]
机构：
[1] College of Intelligent Science and Engineering, Harbin Engineering University, Harbin
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 01期
关键词：
data driven; multi-output support vector regression (SVR); salp swarm algorithm (SSA); vessel trajectory prediction;
D O I：
10.12305/j.issn.1001-506X.2024.01.20
中图分类号：
学科分类号：
摘要：
In order to ensure the rapid, safe and reliable collision avoidance of intelligent vessel, this paper proposes a vessel track prediction model based on the improved salp swarm algorithm (SSA) multi output support vector is proposed. The multi output support vector model used in this paper can model the vessel as a whole, and the vessel model built can predict the changes of vessel track status at the same time. For the super parameters in the model, the improved SSA is used for optimization. The algorithm adds the characteristics of adaptive weight and outlier algorithm, avoiding the problem of premature algorithm and local optimization that is easy to get stuck in high-dimensional. Finally, the proposed method is validated by measured data and compared with other common models. The results show that the proposed method is feasible and effective. © 2024 Chinese Institute of Electronics. All rights reserved.
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页码：173 / 181
页数：8
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