A review on artificial intelligence methodologies for the forecasting of crude oil price

Haruna, Chiroma and Abdul-Kareem, Sameem and Mohd Nor, Ahmad Shukri and Abubakar, Adamu and Safa, Nader Sohrabi and Shuib, Liyana and Hamza, Mukhtar Fatihu and Ya'u Gital, Abdulsalam and Herawan, Tutut (2016) A review on artificial intelligence methodologies for the forecasting of crude oil price. Intelligent Automation & Soft Computing, 22 (3). pp. 449-462. ISSN 1079-8587 E-ISSN 2326-0050

	PDF - Published Version Restricted to Repository staff only Download (1MB) | Request a copy
	PDF Restricted to Registered users only Download (113kB) | Request a copy

Abstract

When crude oil prices began to escalate in the 1970s, conventional methods were the predominant methods used in forecasting oil pricing. These methods can no longer be used to tackle the nonlinear, chaotic, non-stationary, volatile, and complex nature of crude oil prices, because of the methods’ linearity. To address the methodological limitations, computational intelligence techniques and more recently, hybrid intelligent systems have been deployed. In this paper, we present an extensive review of the existing research that has been conducted on applications of computational intelligence algorithms to crude oil price forecasting. Analysis and synthesis of published research in this domain, limitations and strengths of existing studies are provided. This paper finds that conventional methods are still relevant in the domain of crude oil price forecasting and the integration of wavelet analysis and computational intelligence techniques is attracting unprecedented interest from scholars in the domain of crude oil price forecasting. We intend for researchers to use this review as a starting point for further advancement, as well as an exploration of other techniques that have received little or no attention from researchers. Energy demand and supply projection can effectively be tackled with accurate forecasting of crude oil price, which can create stability in the oil market

Item Type:	Article (Review)
Additional Information:	7132/49287
Uncontrolled Keywords:	Crude oil price; Genetic algorithms; Neural networks; Hybrid intelligent systems; Individual intelligent systems; Computational intelligence techniques
Subjects:	Q Science > Q Science (General) > Q300 Cybernetics > Q350 Information theory
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Ahmad Ibrahim Kulliyyah of Laws
Depositing User:	Dr Adamu Abubakar
Date Deposited:	23 Feb 2016 15:51
Last Modified:	19 Dec 2016 15:56
URI:	http://irep.iium.edu.my/id/eprint/49287

Available Versions of this Item

• A review on artificial intelligence methodologies for the forecasting of crude oil price. (deposited 23 Feb 2016 15:51) [Currently Displayed]

Actions (login required)

View Item