基于LSTM的舰船运动姿态短期预测

舰船的六自由度运动状态形成复杂的非线性过程,运动姿态会受到耦合作用、不定周期、噪声信号以及混沌特性等因素的干扰,因此很难得到精确的预测结果.为了提升舰船运动姿态的预测精度,利用舰船时间序列的特点,建立了基于长短期记忆单元(LSTM)模型,对其进行了舰船姿态预测仿真,将结果与时间序列分析法的结果进行对比.实例分析表明:基于LSTM模型的预测方法具有精确度高、易实现的特点.这为舰船运动短期预测提供了一个新的思路和方法.

Short-term prediction of ship motion based on LSTM

The ship motion with six DOF is a complex nonlinear process. It is affected by coupling effect, variable periodicity, noise signal, and the chaos characteristic of ship motion time series so that obtaining precise forecasting results of ship motion is difficult. In order to improve the forecast precision, character of time series in ship motion is analyzed, LSTM model is established and it is used in the emulation research, and the experimental result is compared with the result based on AR model. The result analysis shows that prediction based on LSTM has a high accuracy and is implemented easily, so a new approach is presented for ship motion prediction.