Ship Route Optimization Using Hybrid Physics-Guided Machine Learning
Peer reviewed, Journal article
Published version
Permanent lenke
https://hdl.handle.net/11250/3013472Utgivelsesdato
2022Metadata
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Originalversjon
Journal of Physics: Conference Series (JPCS). 2022, 2311 . 10.1088/1742-6596/2311/1/012037Sammendrag
This paper presents a method for energy efficient weather routing of a ferry in Norway. Historical operational data from the ferry and environmental data are used to develop two models that predict the energy consumption. The first is a purely data-driven linear regression energy model, while the second is as a hybrid model, combining physical models with data-driven models using machine learning techniques. With an established energy model, it is possible to develop a route optimization that proposes efficient routes with less energy usage compared to fixed speed and heading control.