Economic growth forecasting by artificial neural network with extreme learning machine based on trade,import and export parameters |
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| Affiliation: | 1. ISEGI, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal;2. Energy and Environment Modelling Technical Unit, ENEA, Casaccia R. C., Rome, Italy;1. School of Engineering, The University of Tokyo, Japan;2. Financial System and Bank Examination Department, Bank of Japan, Japan;3. Faculty of Economics, The University of Tokyo, Japan;4. Institute for Monetary and Economic Studies, Bank of Japan, Japan |
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| Abstract: | Economic growth may be developed based on trade, imports and exports parameters. The main goal in this study was to predict the economic growth based on trade in services, exports of goods and services, imports of goods and services, trade and merchandise trade on the economic growth. Gross domestic product (GDP) was used as economic growth indicator. The main purpose of this research is to develop and apply the artificial neural network (ANN) with back propagation learning (BP) algorithm and with extreme learning machine (ELM) in order predict GDP growth rate. The aim was to compare the results of BP and ELM prediction accuracy for the GDP growth rate prediction based on the trade data. Based on results, it was demonstrated that ELM can be utilized effectively in applications of GDP growth rate forecasting. |
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| Keywords: | Artificial neural network Extreme learning machine Forecasting Gross domestic product |
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