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http://dx.doi.org/10.5394/KINPR.2019.43.6.335

A Study on the Prediction of Fuel Consumption of a Ship Using the Principal Component Analysis  

Kim, Young-Rong (Graduate School of Korea Maritime and Ocean University)
Kim, Gujong (Korea Maritime Safety Tribunal)
Park, Jun-Bum (Div. of Navigation Science, Korea Maritime and Ocean University)
Publication Information
Journal of Navigation and Port Research / v.43, no.6, 2019 , pp. 335-343 More about this Journal
Abstract
As the regulations of ship exhaust gas have been strengthened recently, many measures are under consideration to reduce fuel consumption. Among them, research has been performed actively to develop a machine-learning model that predicts fuel consumption by using data collected from ships. However, many studies have not considered the methodology of the main parameter selection for the model or the processing of the collected data sufficiently, and the reckless use of data may cause problems such as multicollinearity between variables. In this study, we propose a method to predict the fuel consumption of the ship by using the principal component analysis to solve these problems. The principal component analysis was performed on the operational data of the 13K TEU container ship and the fuel consumption prediction model was implemented by regression analysis with extracted components. As the R-squared value of the model for the test data was 82.99%, this model would be expected to support the decision-making of operators in the voyage planning and contribute to the monitoring of energy-efficient operation of ships during voyages.
Keywords
Ship Fuel Consumption; Energy Efficiency; Principal Component Analysis; Prediction Model; Ship Operational Data;
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Times Cited By KSCI : 1  (Citation Analysis)
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