2 citations · 2 across the 3 of their papers we have counts for
3 papers
Physics-Informed Machine Learning for Vessel Shaft Power and Fuel Consumption Prediction: Interpretable KAN-based Approach
Hamza Haruna Mohammed, Dusica Marijan, Arnbjørn Maressa
Accurate prediction of shaft rotational speed, shaft power, and fuel consumption is crucial for enhancing operational efficiency and sustainability in maritime transportation. Conv…
Physics-guided Neural Network-based Shaft Power Prediction for Vessels
Dogan Altan, Hamza Haruna Mohammed, Glenn Terje Lines +2
Optimizing maritime operations, particularly fuel consumption for vessels, is crucial, considering its significant share in global trade. As fuel consumption is closely related to…
From high-frequency sensors to noon reports: Using transfer learning for shaft power prediction in maritime
Akriti Sharma, Dogan Altan, Dusica Marijan +1
With the growth of global maritime transportation, energy optimization has become crucial for reducing costs and ensuring operational efficiency. Shaft power is the mechanical powe…