Jonas Wallin
Universitetslektor, Studierektor för forskarutbildningen, Statistiska institutionen
Statistical models for the speed prediction of a container ship
Författare
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
Länkar
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