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
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Language:English
Published: The Public Library of Science (PLoS) 2015
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Online Access:http://irep.iium.edu.my/44451/1/PLoS_ONE_published_paper_journal.pone.0136140_%281%29.pdf
http://irep.iium.edu.my/44451/
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0136140
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spelling my.iium.irep.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 REM 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
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
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/44451/1/PLoS_ONE_published_paper_journal.pone.0136140_%281%29.pdf
http://irep.iium.edu.my/44451/
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0136140
_version_ 1643612576280477696
score 13.2014675