Prediction of ship added resistance in waves using an artificial neural network

Abstract

Ship resistance is one of the major components of the ship which hampers its motion. This resistance value experienced by a ship should be known and overcome for the efficient operation of a vessel. This project presents a model to predict added wave resistance experienced through the aid of a Keras sequential artificial neural network. The model is trained with different parameters to enhance its accuracy. A user interface is then linked to this model to attain user inputs and predict the added wave resistance experienced by sea-going vessels.