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Ship Route Optimization Using Hybrid Physics-Guided Machine Learning

Abstract

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.
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Category

Academic article

Language

English

Author(s)

Affiliation

  • SINTEF Group Head Office
  • SINTEF Ocean / Energi og transport

Year

2022

Published in

Journal of Physics: Conference Series (JPCS)

ISSN

1742-6588

Volume

2311

View this publication at Norwegian Research Information Repository