AI-based surrogate model for the prediction of ship fuel consumption reflecting hydrometeorological conditions

statement of authorship
Mingyang Zhang, Nikolaos Tsoulakos, Pentti Kujala, Spyros Hirdaris
source
Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE 2024 ; vol. 9
year of publication
pages
OMAE2024-121992, V009T13A016 ; 11 pages
conference name, date
ASME 2024 : 43rd International Conference on Ocean, Offshore and Arctic Engineering, June 9–14, 2024
conference location
Singapore, Singapore
ISBN
978-0-7918-8787-5
notes
Bibliogr.: 19 ref
Volume 9: Philip Liu Honoring Symposium on Water Wave Mechanics and Hydrodynamics; Blue Economy Symposium
scientific publication
teaduspublikatsioon
TTÜ department
language
inglise
keyword
ship fuel consumption
deep learning method
ship systems
Zhang, M., Tsoulakos, N., Kujala, P., Hirdaris, S. AI-based surrogate model for the prediction of ship fuel consumption reflecting hydrometeorological conditions // Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE 2024 ; vol. 9. : American Society of Mechanical Engineers (ASME), 2024. OMAE2024-121992, V009T13A016 ; 11 pages. https://doi.org/10.1115/OMAE2024-121992