Prediction of Ship Fuel Consumption Due to the Effect of Weather Conditions

The route planning for ship navigation, carried out by navigators and captains, considers various factors, including the weather conditions in the navigated waters. This is because weather conditions are one of the factors that can affect the resistance experienced by the ship. Poor weather conditions can increase the ship’s resistance, resulting in increased fuel consumption and posing a threat to the safety of the ship. Predicting fuel consumption while considering weather conditions is a research topic that has been the focus of many researchers. Various methods, especially artificial intelligence methods, are used for prediction, but the artificial neural network (ANN) method provides the best performance among the methods used. ANN could provide the best performance because it can model the relationships of a complex and nonlinear system, which cannot be converted into mathematical equations. Weather factors have been used as one of the input variables in previous studies, so this paper proposes considering weather factors as disturbance factors. This paper can serve as a guide for researchers to further develop the ANN method as one of the methods for predicting ship fuel consumption while considering weather conditions. The paper presents a comparison of the architectural models of ANN that have been used and how each architecture performs.