Ship roll motion time series forecasting using neural networks

Abstract

A neural network based system has been applied for forecasting the large amplitude roll motions of a ship that appear during parametric roll resonance. Under these conditions, ship roll motion presents a highly nonlinear behavior and accurate predictions are difficult to achieve using classical mathematical modeling approaches. The results obtained present very good agreement to reality, leading to the possibility of applying the system as a base for a parametric roll warning system.