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Jonas Wallin. Foto.

Jonas Wallin

Universitetslektor, Studierektor för forskarutbildningen, Statistiska institutionen

Jonas Wallin. Foto.

Statistical models for the speed prediction of a container ship

Författare

  • Wengang Mao
  • Igor Rychlik
  • Jonas Wallin
  • Gaute Sorhaug

Summary, in English

Accurate prediction of ship speed for given engine power and encountering sea environments is one of the key factors for ship route planning to ensure expected time of arrivals (ETA). Traditional methods need first to compute a ship's total resistance based on theoretical calculations, which are often associated with large uncertainties. In this paper, two statistical approaches are investigated to establish models for a ship's speed prediction. The measurement data of a containership during one year's sailing are used for the demonstration and validation of the presented statistical methods. The pros and cons of the methods are compared in terms of capability, robustness, and accuracy of the prediction. By means of the measured engine Revolutions Per Minute (RPM) and extracted sea environments along the ship's sailing routes, the statistical methods are shown to be able to give reliable speed predictions. Further investigation is needed to test the capability of the statistical methods for the speed prediction using engine power instead of RPM.

Publiceringsår

2016-09-13

Språk

Engelska

Sidor

152-162

Publikation/Tidskrift/Serie

Ocean Engineering

Volym

126

Dokumenttyp

Artikel i tidskrift

Förlag

Elsevier

Ämne

  • Probability Theory and Statistics
  • Marine Engineering

Nyckelord

  • Performance measurement systems
  • Ship speed prediction
  • Engine RPM
  • Regression
  • Autoregressive model
  • Mixed effects model

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1873-5258