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http://dx.doi.org/10.5351/KJAS.2017.30.5.633

A statistical procedure of analyzing container ship operation data for finding fuel consumption patterns  

Kim, Kyung-Jun (Department of Industrial and Management Engineering, Pohang University of Science and Technology)
Lee, Su-Dong (Department of Industrial and Management Engineering, Pohang University of Science and Technology)
Jun, Chi-Hyuck (Department of Industrial and Management Engineering, Pohang University of Science and Technology)
Park, Kae-Myoung (Korean Register of Shipping)
Byeon, Sang-Su (Hyundai Ocean Service CO., LTD.)
Publication Information
The Korean Journal of Applied Statistics / v.30, no.5, 2017 , pp. 633-645 More about this Journal
Abstract
This study proposes a statistical procedure for analyzing container ship operation data that can help determine fuel consumption patterns. We first investigate the features that affect fuel consumption and develop the prediction model to find current fuel consumption. The ship data can be divided into two-type data. One set of operation data includes sea route, voyage information, longitudinal water speed, longitudinal ground speed, and wind, the other includes machinery data such as engine power, rpm, fuel consumption, temperature, and pressure. In this study, we separate the effects of external force on ships according to Beaufort Scale and apply a partial least squares regression to develop a prediction model.
Keywords
ship operation efficiency; Beaufort Scale; PLS regression;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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