The invention belongs to the technical field of ship maneuvering performance prediction, and discloses a ship maneuvering hydrodynamic derivative intelligent forecasting method and system. The method comprises the following steps: compressing a plurality of extracted ship parameters such as a ship three-dimensional geometrical shape, a ship control movement speed and an angular speed into low-dimensional representation data by using a defined auto-encoder, and constructing a physical information neural network model based on the preprocessed compressed low-dimensional representation data; introducing an improved total loss function, and optimizing the physical information neural network model; based on the physical information neural network model with the improved total loss function introduced, a combined training strategy of an optimization algorithm is adopted for further optimization, an optimized physical information neural network model is obtained, and verification and iterative optimization are conducted on the optimized physical information neural network model PINN model. According to the method, high prediction precision can be kept under different working conditions, and good adaptability is shown in complex sea conditions.
本发明属于船舶操纵性能预测技术领域,公开了一种船舶操纵水动力导数智能预报方法及系统。该方法利用定义的自编码器对提取的船舶三维几何形状、船舶操纵运动速度与角速度多个船舶参数压缩至低维表示数据,基于预处理后的压缩后的低维表示数据,构建物理信息神经网络模型;引入改进的总损失函数,优化物理信息神经网络模型;基于引入改进的总损失函数后的物理信息神经网络模型采用优化算法的组合训练策略进行进一步优化,获得优化后的物理信息神经网络模型,对优化后的物理信息神经网络模型PINN模型进行验证与迭代优化。本发明该方法能够在不同的工况下保持较高的预测精度,并在复杂海况中展现出良好的适应性。
Intelligent forecasting method and system for ship control hydrodynamic derivative
一种船舶操纵水动力导数智能预报方法及系统
07.02.2025
Patent
Elektronische Ressource
Chinesisch
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