Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 465, Issue -, Pages 285-288Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2016.08.040
Keywords
GDP; Forecasting; Extreme learning machine; Economic
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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. (C) 2016 Elsevier B.V. All rights reserved.
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