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

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)

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Abstract

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.

Item Type:	Article (Journal)
Additional Information:	7132/44451
Uncontrolled Keywords:	OPEC, Carbon Dioxide, Emissions, Petroleum Consumption, Neural Network, Hybrid Cuckoo Search.
Subjects:	Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
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:	27 Aug 2015 12:40
Last Modified:	27 Oct 2015 16:18
URI:	http://irep.iium.edu.my/id/eprint/44451

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