Artificial Intelligence Techniques for the Forecasting of Crude Oil Price: A Literature Review









Abstract

Forecasting crude oil prices is a subject that is of vital importance throughout the world. Economic conditions, organizational activities, and decision-making are affected by changes in the price of this commodity. A literature review of selected academic work conducted between 2010 and 2022 has been conducted to address the latest trends in Artificial Intelligence (AI) algorithms for forecasting oil prices. Several related published papers were explored using Google Scholar and the Connected Paper Online applications. According to recently released research, traditional approaches to predicting crude oil prices are still applicable and multi-AI algorithm approaches are becoming more prevalent. Among the published papers that have been reviewed, artificial neural networks (ANN) and support vector machines (SVMs) appear to be the most commonly used AI techniques. Researchers can build on this review to explore underutilized techniques, which have received only limited or no attention from the scientific community.


Modules


Algorithms


Software And Hardware