Title: Soft computing approach for predicting OPEC countries' oil consumption

Authors: Haruna Chiroma; Adamu I. Abubakar; Tutut Herawan

Addresses: Department of Computer Science, Federal College of Education (Technical), Gombe, Nigeria; Department of Artificial Intelligence, Faculty of Computer Science and IT, University of Malaya, Malaysia ' Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia ' Department of Information Systems, Faculty of Computer Science and IT, University of Malaya, Malaysia

Abstract: Human activities in today's modern world would not be possible without oil. The oil consumed by the Organization of the Petroleum Exporting Countries (OPEC) has increased significantly. Several soft computing models exist for oil consumption modelling. However, the models are deficient in terms of predicting oil consumed by an OPEC country on the basis of the other OPEC countries' oil consumption. In this paper, a soft computing method is proposed for predicting oil consumption in OPEC countries. The significant, positive relationship among the oil consumption values of OPEC countries is also investigated. It was found that it is possible to predict the oil consumption of any OPEC country on the basis of the oil consumption of other OPEC countries with minimum and maximum accuracy of 94.63% and 97.10%, respectively. Statistical result validation clearly shows that the oil consumption predicted with the proposed model and the actual oil consumption are equal. The findings of this research can be applied for the efficient formulation of policies related to oil. Furthermore, oil consumption prediction is required for the management of greenhouse emissions, the creation of effective risk management frameworks, and revenue generation analysis. [Received: January 8, 2015; Accepted: November 23, 2015]

Keywords: oil consumption; policy; Organization of the Petroleum Exporting Countries; OPEC countries; soft computing.

DOI: 10.1504/IJOGCT.2017.084435

International Journal of Oil, Gas and Coal Technology, 2017 Vol.15 No.3, pp.298 - 316

Available online: 30 May 2017 *

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