基于改进多输出支持向量的船舶航迹预测

doi:10.12305/j.issn.1001-506X.2024.01.20

Abstract

Abstract:

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.

Key words: multi-output support vector regression (SVR), salp swarm algorithm (SSA), vessel trajectory prediction, data driven

CLC Number:

TP181

Zhenya YANG, Zhi ZHANG, Xiaobing SHANG, Zejun CAO, Zhexuan SUN. Vessel trajectory prediction based on improved multi-output support vector[J]. Systems Engineering and Electronics, 2023, 46(1): 173-181.

Figures/Tables 10

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References 30

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Lat	Lon	Sog	Sin	Cos	时间/s
0.666 87	0.238 80	0.007 732	0.131 951	0.161 562	0.103 5
0.666 89	0.238 80	0.005 155	0.203 993	0.097 036	0.001 7
0.666 90	0.238 80	0.007 732	0.108 696	0.188 743	0.001 6

船舶轨迹模型	e_jMS		r_j		COV
船舶轨迹模型	最坏	最好	最坏	最好	最坏	最好
SSALSSVM	0.009 39	3.28E-06	0.971 87	0.999 18	3.91E-06	1.64E-07
PSOSVR	0.008 96	9.99E-06	0.854 28	0.983 45	1.75E-06	6.90E-07
GRIMLSSVM	0.004 52	5.50E-05	0.905 41	0.998 73	5.15E-08	1.93E-08
SSAMLSSVR	0.002 68	5.59E-06	0.990 43	0.999 87	9.83E-08	2.68E-10

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Vessel trajectory prediction based on improved multi-output support vector

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