Article
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Preserved in Portico This version is not peer-reviewed
Spot Charter Rate Forecast for Liquefied Natural Gas Carriers
Version 1
: Received: 22 July 2022 / Approved: 26 July 2022 / Online: 26 July 2022 (03:50:12 CEST)
A peer-reviewed article of this Preprint also exists.
Lyridis, D.V. Spot Charter Rate Forecast for Liquefied Natural Gas Carriers. J. Mar. Sci. Eng. 2022, 10, 1270. Lyridis, D.V. Spot Charter Rate Forecast for Liquefied Natural Gas Carriers. J. Mar. Sci. Eng. 2022, 10, 1270.
Abstract
Recent maritime legislations demand the transformation of the sector to greener and more energy efficient transportation. Liquified Natural Gas (LNG) seems a promising alternative fuel solution that could replace the conventional fuel sources. Various studies have been focused on the prediction of LNG price, however, no previous work has been made on the forecast of spot charter rate of LNG carrier ships. An important knowledge for the maritime industries and companies when it comes to decision-making. Therefore, this study is focused on the development of a machine learning pipeline to address the aforementioned problem by: (i) forming a dataset with variables relevant to LNG; (ii) identifying the variables that impact on the freight price of LNG carrier; (iii) developing and evaluating regression models for short and mid-term forecast. The results showed that the General Regression Neural Network presented a stable overall performance for 2, 4 and 6 months forecast.
Keywords
machine learning; forecast; regression models; Liquified Natural Gas; maritime transportation
Subject
Engineering, Marine Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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