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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.

Category

Academic article

Client

  • Research Council of Norway (RCN) / 295763

Language

English

Affiliation

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

Year

2022

Published in

Journal of Physics: Conference Series (JPCS)

ISSN

1742-6588

Publisher

IOP Publishing

Volume

2311

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