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

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...

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Main Authors:	Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saudi, Younes, Hamza, Mukhtar Fatihu, Shuiba, Liyana, Gital, Abdulsalam, Herawan, Tutut
Format:	Article
Language:	English English
Published:	Elsevier 2016
Subjects:	QA76 Computer software
Online Access:	http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/1/A_new_approach_for_forecasting_OPEC_petroleum_consumption_based_on_neural_network_train_by_using_flowerpollination_algorithm.pdf http://irep.iium.edu.my/51477/4/51477_A_new_approach_for_forecasting_OPEC_petroleum_SCOPUS.pdf

id	iium-51477
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spelling	iium-514772017-01-17T08:21:04Z http://irep.iium.edu.my/51477/ A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saudi, Younes Hamza, Mukhtar Fatihu Shuiba, Liyana Gital, Abdulsalam Herawan, Tutut QA76 Computer software 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. Elsevier 2016-11 Article PeerReviewed application/pdf en http://irep.iium.edu.my/51477/1/A_new_approach_for_forecasting_OPEC_petroleum_consumption_based_on_neural_network_train_by_using_flowerpollination_algorithm.pdf application/pdf en http://irep.iium.edu.my/51477/4/51477_A_new_approach_for_forecasting_OPEC_petroleum_SCOPUS.pdf 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 http://www.sciencedirect.com/science/article/pii/S1568494616303180 10.1016/j.asoc.2016.06.038
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saudi, Younes Hamza, Mukhtar Fatihu Shuiba, Liyana Gital, Abdulsalam Herawan, Tutut A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
description	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.
format	Article
author	Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saudi, Younes Hamza, Mukhtar Fatihu Shuiba, Liyana Gital, Abdulsalam Herawan, Tutut
author_facet	Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saudi, Younes Hamza, Mukhtar Fatihu Shuiba, Liyana Gital, Abdulsalam Herawan, Tutut
author_sort	Haruna, Chiroma
title	A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
title_short	A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
title_full	A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
title_fullStr	A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
title_full_unstemmed	A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
title_sort	new approach for forecasting opec petroleum consumption based on neural network train by using flower pollination algorithm
publisher	Elsevier
publishDate	2016
url	http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/ http://irep.iium.edu.my/51477/1/A_new_approach_for_forecasting_OPEC_petroleum_consumption_based_on_neural_network_train_by_using_flowerpollination_algorithm.pdf http://irep.iium.edu.my/51477/4/51477_A_new_approach_for_forecasting_OPEC_petroleum_SCOPUS.pdf
first_indexed	2023-09-18T21:12:52Z
last_indexed	2023-09-18T21:12:52Z
_version_	1777411369082028032

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

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