title: Global Warming: Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption Using Neural Network and Hybrid Cuckoo Search Algorithm.
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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia; School of Science, Department of Computer Science, Federal College of Education (Technical), Gombe, Nigeria.
authors: Haruna
authors: H
authors: Chiroma
authors: Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia.
authors: Sameem
authors: S
authors: Abdul-kareem
authors: Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
authors: Abdullah
authors: A
authors: Khan
authors: Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
authors: Nazri Mohd
authors: NM
authors: Nawi
authors: Faculty of Computing, University Technology Malaysia, Johor Bahru, Malaysia.
authors: Abdulsalam Ya'u
authors: AY
authors: Gital
authors: Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia.
authors: Liyana
authors: L
authors: Shuib
authors: Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
authors: Adamu I
authors: AI
authors: Abubakar
authors: Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
authors: Muhammad Zubair
authors: MZ
authors: Rahman
authors: Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia.
authors: Tutut
authors: T
authors: Herawan
mesh_terms: D000465:Algorithms; D002245:Carbon Dioxide / Q000032:analysis*; D057232:Global Warming; D006801:Humans; D016571:Neural Networks, Computer; D010578:Petroleum
chemical_list: D010578:Petroleum; D002245:Carbon Dioxide