A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm

Haruna, Chiroma and Khan, Abdullah and Abubakar, Adamu and Saudi, Younes and Hamza, Mukhtar Fatihu and Shuiba, Liyana and Gital, Abdulsalam and Herawan, Tutut (2016) A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm. Applied Soft Computing, 48 (November 2016). pp. 50-58. ISSN 1568-4946

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Abstract

Petroleum is the live wire of modern technology and its operations, with economic development being positively linked to petroleum consumption. Many meta-heuristic algorithms have been proposed in literature for the optimization of Neural Network (NN) to build a forecasting model. In this paper, as an alternative to previous methods, we propose a new flower pollination algorithm with remarkable balance between consistency and exploration for NN training to build a model for the forecasting of petroleum consumption by the Organization of the Petroleum Exporting Countries (OPEC). The proposed approach is compared with established meta-heuristic algorithms. The results show that the new proposed method out performs existing algorithms by advancing OPEC petroleum consumption forecast accuracy and convergence speed. Our proposed method has the potential to be used as an important tool in forecasting OPEC petroleum consumption to be used by OPEC authorities and other global oil-related organizations.This will facilitate proper monitoring and control of OPEC petroleum consumption.

Item Type:	Article (Journal)
Additional Information:	7132/51477
Uncontrolled Keywords:	Flower pollination algorithm, Neural network, Accelerated particle swarm optimization, Organization of the petroleum exporting countries (OPEC), Energy, Petroleum consumption
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Dr Adamu Abubakar
Date Deposited:	09 Aug 2016 14:38
Last Modified:	17 Jan 2017 16:21
URI:	http://irep.iium.edu.my/id/eprint/51477

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