Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm

Background Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be c...

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Main Authors:	Haruna, Chiroma, Abdul-Kareem, Sameem, Mohd Nawi, Nazri, Gital, Abdulsam Ya'u, Shuib, Liyana, Abubakar, Adamu, Rahman, Muhammad Zubair, Herawan, Tutut
Format:	Article
Language:	English
Published:	The Public Library of Science (PLoS) 2015
Subjects:	Z665 Library Science. Information Science
Online Access:	http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/1/PLoS_ONE_published_paper_journal.pone.0136140_%281%29.pdf

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spelling	iium-444512015-10-27T08:18:04Z http://irep.iium.edu.my/44451/ Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm Haruna, Chiroma Abdul-Kareem, Sameem Mohd Nawi, Nazri Gital, Abdulsam Ya'u Shuib, Liyana Abubakar, Adamu Rahman, Muhammad Zubair Herawan, Tutut Z665 Library Science. Information Science Background Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be caused by the emissions of greenhouse gases due to human activities including the emissions of carbon dioxide (CO2) from petroleum consumption. Limitations of the previous methods of predicting CO2 emissions and lack of work on the prediction of the Organization of the Petroleum Exporting Countries (OPEC) CO2 emissions from petroleum consumption have motivated this research. Methods/Findings The OPEC CO2 emissions data were collected from the Energy Information Administration. Artificial Neural Network (ANN) adaptability and performance motivated its choice for this study. To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. The proposed model predicts OPEC CO2 emissions for 3, 6, 9, 12 and 16 years with an improved accuracy and speed over the state-of-the-art methods. Conclusion An accurate prediction of OPEC CO2 emissions can serve as a reference point for propagating the reorganisation of economic development in OPEC member countries with the view of reducing CO2 emissions to Kyoto benchmarks—hence, reducing global warming. The policy implications are discussed in the paper. The Public Library of Science (PLoS) 2015-08-25 Article PeerReviewed application/pdf en http://irep.iium.edu.my/44451/1/PLoS_ONE_published_paper_journal.pone.0136140_%281%29.pdf Haruna, Chiroma and Abdul-Kareem, Sameem and Mohd Nawi, Nazri and Gital, Abdulsam Ya'u and Shuib, Liyana and Abubakar, Adamu and Rahman, Muhammad Zubair and Herawan, Tutut (2015) Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm. PLoS ONE, 10 (8). pp. 1-21. ISSN 1932-6203 (P) 1932-6203 (O) http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0136140 e0136140. doi:10.1371/journal.pone.0136140
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	Z665 Library Science. Information Science
spellingShingle	Z665 Library Science. Information Science Haruna, Chiroma Abdul-Kareem, Sameem Mohd Nawi, Nazri Gital, Abdulsam Ya'u Shuib, Liyana Abubakar, Adamu Rahman, Muhammad Zubair Herawan, Tutut Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
description	Background Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be caused by the emissions of greenhouse gases due to human activities including the emissions of carbon dioxide (CO2) from petroleum consumption. Limitations of the previous methods of predicting CO2 emissions and lack of work on the prediction of the Organization of the Petroleum Exporting Countries (OPEC) CO2 emissions from petroleum consumption have motivated this research. Methods/Findings The OPEC CO2 emissions data were collected from the Energy Information Administration. Artificial Neural Network (ANN) adaptability and performance motivated its choice for this study. To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. The proposed model predicts OPEC CO2 emissions for 3, 6, 9, 12 and 16 years with an improved accuracy and speed over the state-of-the-art methods. Conclusion An accurate prediction of OPEC CO2 emissions can serve as a reference point for propagating the reorganisation of economic development in OPEC member countries with the view of reducing CO2 emissions to Kyoto benchmarks—hence, reducing global warming. The policy implications are discussed in the paper.
format	Article
author	Haruna, Chiroma Abdul-Kareem, Sameem Mohd Nawi, Nazri Gital, Abdulsam Ya'u Shuib, Liyana Abubakar, Adamu Rahman, Muhammad Zubair Herawan, Tutut
author_facet	Haruna, Chiroma Abdul-Kareem, Sameem Mohd Nawi, Nazri Gital, Abdulsam Ya'u Shuib, Liyana Abubakar, Adamu Rahman, Muhammad Zubair Herawan, Tutut
author_sort	Haruna, Chiroma
title	Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
title_short	Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
title_full	Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
title_fullStr	Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
title_full_unstemmed	Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
title_sort	global warming: predicting opec carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
publisher	The Public Library of Science (PLoS)
publishDate	2015
url	http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/ http://irep.iium.edu.my/44451/1/PLoS_ONE_published_paper_journal.pone.0136140_%281%29.pdf
first_indexed	2023-09-18T21:03:11Z
last_indexed	2023-09-18T21:03:11Z
_version_	1777410760493760512

Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm

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