船舶运动姿态的准确预测对船舶的运动补偿意义重大，因此提出一种基于变分模态分解（VMD）和麻雀搜索算法（SSA）优化门控循环单元（GRU）的船舶运动姿态预测模型。首先利用VMD将船舶运动姿态数据分解为若干个本征模态分量，然后对各个本征模态分量分别建立SSA-GRU预测模型进行预测，最后累加得到预测结果。通过实船模拟的船舶运动姿态数据进行验证，证明此预测模型较于SSA-GRU和GRU预测模型预测精度均有相应提升，验证了本预测模型在船舶运动姿态数据预测的有效性。
The accurate prediction of ship motion attitude is of great significance to ship motion compensation. Therefore, a ship motion attitude prediction model based on variational modal decomposition (VMD) and sparrow search algorithm (SSA) to optimize the gated recurrent unit (GRU) is proposed. Firstly, the ship motion attitude data is decomposed into several eigenmode components by VMD, Then, the ssa-gru prediction model is established for each eigenmode component to predict, and finally the prediction results are accumulated. Through the verification of the ship motion attitude data simulated by the real ship, the experiment shows that the prediction accuracy of this prediction model is improved compared with ssa-gru and Gru prediction models, and the effectiveness of this prediction model in the prediction of ship motion attitude data is verified.
2022,44(23): 60-65 收稿日期：2021-08-03
DOI：10.3404/j.issn.1672-7649.2022.23.012
分类号：U661.32
作者简介：左思雨(1997-)，女，硕士研究生，研究方向为船舶运动姿态预测
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