Data science and advanced analytics for shipping energy systems

Andrea Coraddu, Miltiadis Kalikatzarakis, Jake Walker, Davide Ilardi, Luca Oneto

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review

2 Citations (Scopus)
91 Downloads (Pure)

Abstract

The purpose of this chapter is to provide an overview of the state-of-the-art and future perspectives of Data Science and Advanced Analytics for Shipping Energy Systems. Specifically, we will start by listing the different static and dynamic data sources and knowledge base available in this particular context. Then we will review the Data Science and Advanced Analytics technologies that can leverage these data to extract and synthesize new additional actionable information, suggestions, and actions. We will then review the current exploitation strategies of these technologies aiming at improving the current Shipping Energy Systems. In conclusion, we will depict our vision on the future perspectives of the application and adoption of Data Science and Advanced Analytics for shaping the next generations of Shipping Energy Systems.

Original languageEnglish
Title of host publicationSustainable Energy Systems on Ships
Subtitle of host publicationNovel Technologies for Low Carbon Shipping
EditorsFrancesco Baldi, Andrea Coraddu, Maria E. Mondejar
PublisherElsevier
Chapter7
Pages303-349
ISBN (Electronic)978-0-12-824471-5
ISBN (Print)978-0-32-385990-5
DOIs
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Advanced analytics
  • Artificial intelligence
  • Data mining
  • Data science
  • Machine learning (ML)
  • Shipping energy systems

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