为保障智能船舶快速、安全、可靠地进行避碰工作,提出了一种基于改进樽海鞘群算法(salp swarm algorithm,SSA)的多输出支持向量的船舶航迹预测模型.本文采用的多输出支持向量模型可以对船舶进行整体建模,所构建的模型可以对船舶航迹状态进行多输出预测,对于模型中存在的超参数采用改进的SSA进行寻优,算法加入了自适应权重与离群象算法,避免了算法早熟与高维易陷入局部最优的问题.最后,实验选取了实测数据对所提方法进行验证,并与其他常见模型进行对比实验,结果表明了所提方法的可行性与有效性.
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.