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Gross domestic product estimation based on electricity utilization by artificial neural network

Author

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  • Stevanović, Mirjana
  • Vujičić, Slađana
  • Gajić, Aleksandar M.

Abstract

The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.

Suggested Citation

  • Stevanović, Mirjana & Vujičić, Slađana & Gajić, Aleksandar M., 2018. "Gross domestic product estimation based on electricity utilization by artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 28-31.
    • Handle: RePEc:eee:phsmap:v:489:y:2018:i:c:p:28-31
    DOI: 10.1016/j.physa.2017.07.023
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    References listed on IDEAS

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    1. Osman, Mohamed & Gachino, Geoffrey & Hoque, Ariful, 2016. "Electricity consumption and economic growth in the GCC countries: Panel data analysis," Energy Policy, Elsevier, vol. 98(C), pages 318-327.
    2. Hamdi, Helmi & Sbia, Rashid & Shahbaz, Muhammad, 2014. "The nexus between electricity consumption and economic growth in Bahrain," Economic Modelling, Elsevier, vol. 38(C), pages 227-237.
    3. He, Yiming & Fullerton, Thomas M. & Walke, Adam G., 2017. "Electricity consumption and metropolitan economic performance in Guangzhou: 1950–2013," Energy Economics, Elsevier, vol. 63(C), pages 154-160.
    4. Sarwar, Suleman & Chen, Wei & Waheed, Rida, 2017. "Electricity consumption, oil price and economic growth: Global perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 9-18.
    5. Ge, Fei & Ye, Bin & Xing, Shengnan & Wang, Bao & Sun, Shuang, 2017. "The analysis of the underlying reasons of the inconsistent relationship between economic growth and the consumption of electricity in China – A case study of Anhui province," Energy, Elsevier, vol. 128(C), pages 601-608.
    6. Bélaïd, Fateh & Youssef, Meriem, 2017. "Environmental degradation, renewable and non-renewable electricity consumption, and economic growth: Assessing the evidence from Algeria," Energy Policy, Elsevier, vol. 102(C), pages 277-287.
    7. Dogan, Eyup, 2015. "The relationship between economic growth and electricity consumption from renewable and non-renewable sources: A study of Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 534-546.
    8. Shahbaz, Muhammad & Sarwar, Suleman & Chen, Wei & Malik, Muhammad Nasir, 2017. "Dynamics of electricity consumption, oil price and economic growth: Global perspective," Energy Policy, Elsevier, vol. 108(C), pages 256-270.
    9. Brini, Riadh & Amara, Mohamed & Jemmali, Hatem, 2017. "Renewable energy consumption, International trade, oil price and economic growth inter-linkages: The case of Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 620-627.
    10. Mezghani, Imed & Ben Haddad, Hedi, 2017. "Energy consumption and economic growth: An empirical study of the electricity consumption in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 145-156.
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    3. Tümer, Abdullah Erdal & Akkuş, Aytekin, 2018. "Forecasting Gross Domestic Product per Capita Using Artificial Neural Networks with Non-Economical Parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 468-473.

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