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Forecasting LNG Freight rate with Artificial Neural Networks

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(7), pp.187-194
  • DOI : 10.9708/jksci.2022.27.07.187
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 5, 2022
  • Accepted : July 26, 2022
  • Published : July 29, 2022

Sangseop Lim 1 Young-Joong Ahn 1

1한국해양대학교

Accredited

ABSTRACT

LNG is known as the transitional energy source for the future eco-friendly, attracting enormous market attention due to global eco-friendly regulations, Covid-19 Pandemic, Russia-Ukraine War. In addition, since new LNG suppliers such as the U.S. and Australia are also diversifying, the LNG spot market is expected to grow. On the other hand, research on the LNG transportation market has been marginalized. Therefore, this study attempted to predict short-term LNG 160K spot rates and compared the prediction performance between artificial neural networks and the ARIMA model. As a result of this paper, while it was difficult to determine the superiority and superiority of ARIMA and artificial neural networks, considering the relative free of ANN's contraints, we confirmed the feasibility of ANN in LNG 160K spot rate prediction. This study has academic significance as the first attempt to apply an artificial neural network to forecasting LNG 160K spot rates and are expected to contribute significantly in practice in that they can improve the quality of short-term investment decisions by market participants by increasing the accuracy of short-term prediction.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.