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Quality & Quantity

, Volume 51, Issue 3, pp 1395–1401 | Cite as

RETRACTED ARTICLE: Prediction of economic growth by extreme learning approach based on science and technology transfer

  • Petra Karanikić
  • Igor MladenovićEmail author
  • Svetlana Sokolov-Mladenović
  • Meysam Alizamir
Article

Abstract

The purpose of this research is to develop and apply the extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. Economic growth may be developed on the basis on combination of different factors. In this investigation was analyzed the economic growth prediction based on the science and technology transfer. The main goal was to analyze the influence of number of granted European patents on the economic growth by field of technology. GDP was used as economic growth indicator. The ELM results are compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models were accessed based on simulation results and using several statistical indicators. Coefficient of determination for ELM method is 0.9841, for ANN method it is 0.7956 and for the GP method it is 0.7561. Based upon simulation results, it is demonstrated that ELM can be utilized effectively in applications of GDP forecasting.

Keywords

GDP Forecasting Extreme learning machine Economic growth 

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Petra Karanikić
    • 1
  • Igor Mladenović
    • 2
    Email author
  • Svetlana Sokolov-Mladenović
    • 2
  • Meysam Alizamir
    • 3
  1. 1.Department of BiotechnologyUniversity of RijekaRijekaCroatia
  2. 2.University of Niš, Faculty of EconomicsNišSerbia
  3. 3.Young Researchers and Elites Club, Hamedan BranchIslamic Azad UniversityHamedanIran

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