Real time prediction of ship motion for the aid of helicopter and aircraft deployment and recovery

Due to the random nature of the ship's motion in an open water environment, the deployment and the landing of air vehicles from a ship can often be difficult and even dangerous. The ability to reliably predict the motion will allow improvements in safety on board ships and facilitate more accurate deployment of vehicles off ships. This paper presents an investigation into the application of artificial neural network methods trained using singular value decomposition and genetic algorithms for the prediction of ship motion. It is shown that the artificial neural network produces excellent predictions and is able to predict the ship motion satisfactorily for up to 7 seconds.