Advanced Machine Learning for Ship Resistance Prediction
Year: 2026
Type: article
Abstract: Ship resistance strongly influences fuel consumption and greenhouse gas emissions Traditional semi empiricalformulas (e g ITTC/Holtrop simplify complex physics and may miss nonlinear interactions across diverse hull shapesMachine learning can model nonlinear relationships, but purely data driven models often lack physical interpretabilityand may not generalize across different hull families Our approach combines physics with machine learning wepredict resistance components (e g frictional and wave and recombine them using physics based methods to maintaininterpretability and constraints
Author: Moon, Mahin Hasan
Institution: Bangladesh University of Engineering and Technology
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7128960545
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