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Mathematics
Volume 10
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10.3390/math10224361
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Article

Artificial Intelligence-Based Prediction of Crude Oil Prices Using Multiple Features under the Effect of Russia–Ukraine War and COVID-19 Pandemic

by
Hadi Jahanshahi
1,*,
Süleyman Uzun
2,
Sezgin Kaçar
3,
Qijia Yao
4 and
Madini O. Alassafi
5
1
Department of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
2
Computer Engineering Department, Technology Faculty, Sakarya University of Applied Sciences, Sakarya 54050, Turkey
3
Electrical and Electronics Engineering Department, Technology Faculty, Sakarya University of Applied Sciences, Sakarya 54050, Turkey
4
School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
5
Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
*
Author to whom correspondence should be addressed.
Mathematics 2022, 10(22), 4361; https://doi.org/10.3390/math10224361
Submission received: 28 October 2022 / Revised: 16 November 2022 / Accepted: 18 November 2022 / Published: 20 November 2022
(This article belongs to the Special Issue Application of Mathematical Methods in Financial Economics)
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Abstract

The effect of the COVID-19 pandemic on crude oil prices just faded; at this moment, the Russia–Ukraine war brought a new crisis. In this paper, a new application is developed that predicts the change in crude oil prices by incorporating these two global effects. Unlike most existing studies, this work uses a dataset that involves data collected over twenty-two years and contains seven different features, such as crude oil opening, closing, intraday highest value, and intraday lowest value. This work applies cross-validation to predict the crude oil prices by using machine learning algorithms (support vector machine, linear regression, and rain forest) and deep learning algorithms (long short-term memory and bidirectional long short-term memory). The results obtained by machine learning and deep learning algorithms are compared. Lastly, the high-performance estimation can be achieved in this work with the average mean absolute error value over 0.3786.
Keywords: prediction of crude oil prices; COVID-19 effect; Russia–Ukraine war effect; machine learning; deep learning; time series forecasting prediction of crude oil prices; COVID-19 effect; Russia–Ukraine war effect; machine learning; deep learning; time series forecasting

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MDPI and ACS Style

Jahanshahi, H.; Uzun, S.; Kaçar, S.; Yao, Q.; Alassafi, M.O. Artificial Intelligence-Based Prediction of Crude Oil Prices Using Multiple Features under the Effect of Russia–Ukraine War and COVID-19 Pandemic. Mathematics 2022, 10, 4361. https://doi.org/10.3390/math10224361

AMA Style

Jahanshahi H, Uzun S, Kaçar S, Yao Q, Alassafi MO. Artificial Intelligence-Based Prediction of Crude Oil Prices Using Multiple Features under the Effect of Russia–Ukraine War and COVID-19 Pandemic. Mathematics. 2022; 10(22):4361. https://doi.org/10.3390/math10224361

Chicago/Turabian Style

Jahanshahi, Hadi, Süleyman Uzun, Sezgin Kaçar, Qijia Yao, and Madini O. Alassafi. 2022. "Artificial Intelligence-Based Prediction of Crude Oil Prices Using Multiple Features under the Effect of Russia–Ukraine War and COVID-19 Pandemic" Mathematics 10, no. 22: 4361. https://doi.org/10.3390/math10224361

APA Style

Jahanshahi, H., Uzun, S., Kaçar, S., Yao, Q., & Alassafi, M. O. (2022). Artificial Intelligence-Based Prediction of Crude Oil Prices Using Multiple Features under the Effect of Russia–Ukraine War and COVID-19 Pandemic. Mathematics, 10(22), 4361. https://doi.org/10.3390/math10224361

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