Prediction of Ship Roll Based on Second Diagonal Recurrent Neural Network

An optimized second diagonal recurrent neural network is proposed to develop a model of prediction of ship rolling motion. This approach is based on an algorithm of optimization second diagonal recurrent neural networks （OSDRNN）. The stochastic gradient descent algorithm is used to optimize parameters of this network. Using this model to predict the situation of one certain type of ship sailing in the beam sea condition, simulation results show that the optimization of this network improves network performance and the generalization performance of the network, and it has higher prediction on the accuracy and forecast rate. The presented network model used in contrast to SDRNN model can quickly and accurately predict the time series of shio rollinz.