舰船运动是引发多种海面事故的主要原因,为了提高舰载机着舰安全系数、提高舰船战斗力、减少海难等事故的发生,舰船运动极短期预报是至关重要的.首次将CMAC神经网络应用于舰船纵摇运动姿态的极短期预报中,建立了CMAC神经网络舰船运动预报模型.同时对实际的舰船纵摇运动数据进行了数值仿真,证实了CMAC神经网络模型在舰船运动预报中的应用是合理且可行的. Ship movement is the main cause of various sea accidents. In order to improve the safety factor of carrier-based aircraft and enhance the combat effectiveness of ships and reduce accidents such as shipwreck, extremely short-term forecast of ship motion is crucial. For the first time, CMAC Neural network is applied to the very short-term forecast of the ship’s pitch motion attitude, and a CMAC neural network model of ship motion forecasting is established. At the same time, the actual ship pitch motion data are numerically simulated, which confirms that CMAC neural network model The application of ship motion forecasting is reasonable and feasible.