Application of artificial neural network with extreme learning machine for economic growth estimation
Tanja Vujović and
Physica A: Statistical Mechanics and its Applications, 2017, vol. 465, issue C, 285-288
The purpose of this research is to develop and apply the artificial neural network (ANN) with extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. The economic growth forecasting was analyzed based on agriculture, manufacturing, industry and services value added in GDP. The results were compared with ANN with back propagation (BP) learning approach since BP could be considered as conventional learning methodology. The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Based on results, it was shown that ANN with ELM learning methodology can be applied effectively in applications of GDP forecasting.
Keywords: GDP; Forecasting; Extreme learning machine; Economic (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:465:y:2017:i:c:p:285-288
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