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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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    3. Hemmat Esfe, Mohammad & Kamyab, Mohammad Hassan & Afrand, Masoud & Amiri, Mahmoud Kiannejad, 2018. "Using artificial neural network for investigating of concurrent effects of multi-walled carbon nanotubes and alumina nanoparticles on the viscosity of 10W-40 engine oil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 610-624.

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