Global Warming: Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption Using Neural Network and Hybrid Cuckoo Search Algorithm.

Journal: PloS one
Published Date: Aug 25, 2015

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.

Authors

  • Haruna Chiroma
    Future Technology Research Center, National Yunlin University of Science and Technology, Yulin, Taiwan.
  • Sameem Abdul-kareem
    Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia.
  • Abdullah Khan
    Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
  • Nazri Mohd Nawi
    Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
  • Abdulsalam Ya'u Gital
    Faculty of Computing, University Technology Malaysia, Johor Bahru, Malaysia.
  • Liyana Shuib
    Department of Information System, Universiti Malaya, Kuala Lumpur, Malaysia.
  • Adamu I Abubakar
    Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia.
  • Muhammad Zubair Rahman
    Software and multimedia center faculty of science and computer technology, University Tun Hussein Onn, Johor Bahru, Malaysia.
  • Tutut Herawan
    Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia.

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