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Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship
Citation
Yan, R and Wang, S and Du, Y, Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship, Transportation Research Part E: Logistics and Transportation Review, 138 Article 101930. ISSN 1366-5545 (2020) [Refereed Article]
Copyright Statement
© 2020 Elsevier Ltd. All rights reserved.
Official URL: https://www-sciencedirect-com.ezproxy.utas.edu.au/...
DOI: doi:10.1016/j.tre.2020.101930
Abstract
Shipping industry is the backbone of global trade. However, the large quantities of greenhouse gas emissions from shipping, such as carbon dioxide (CO2), cannot be ignored. In order to comply with the international environmental regulations as well as to increase commercial profits, shipping companies have stronger motivations to improve ship energy efficiency. In this study, a two-stage ship fuel consumption prediction and reduction model is proposed for a dry bulk ship. At the first stage, a fuel consumption prediction model based on random forest regressor is proposed and validated. The prediction model takes into account ship sailing speed, total cargo weight, and sea and weather conditions and then predicts hourly fuel consumption of the main engine. The mean absolute percentage error of the random forest regressor is 7.91%. At the second stage, a speed optimization model is developed based on the prediction model proposed at the first stage while guaranteeing the estimated arrival time to the destination port. Numerical experiment on two consecutive-8-day voyages shows that the proposed model can reduce ship fuel consumption by 2–7%. The reduction in ship fuel consumption will also lead to lower CO2 emissions.
Item Details
Item Type: | Refereed Article |
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Keywords: | fuel consumption prediction, ship fuel efficiency, ship speed optimization, random forest regressor, machine learning |
Research Division: | Commerce, Management, Tourism and Services |
Research Group: | Transportation, logistics and supply chains |
Research Field: | Maritime transportation and freight services |
Objective Division: | Transport |
Objective Group: | Water transport |
Objective Field: | International sea freight transport (excl. live animals, food products and liquefied gas) |
UTAS Author: | Du, Y (Dr Bill Du) |
ID Code: | 138824 |
Year Published: | 2020 |
Web of Science® Times Cited: | 33 |
Deposited By: | Maritime and Logistics Management |
Deposited On: | 2020-04-30 |
Last Modified: | 2020-07-30 |
Downloads: | 4 View Download Statistics |
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