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**Harvard**

Mao, W., Wallin, J. och Rychlik, I. (2016) * Statistical models for the speed prediction of a container ship*.

** BibTeX **

@article{

Mao2016,

author={Mao, Wengang and Wallin, Jonas and Rychlik, Igor},

title={ Statistical models for the speed prediction of a container ship},

journal={Ocean Engineering},

issn={0029-8018},

volume={126},

pages={152-162},

abstract={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.},

year={2016},

keywords={ Performance measurement; Ship speed prediction; Engine RPM; Regression; Autoregressive model; Mixed effects model},

}

** RefWorks **

RT Journal Article

SR Print

ID 242091

A1 Mao, Wengang

A1 Wallin, Jonas

A1 Rychlik, Igor

T1 Statistical models for the speed prediction of a container ship

YR 2016

JF Ocean Engineering

SN 0029-8018

VO 126

SP 152

OP 162

AB 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.

LA eng

OL 30