FORECASTING ALGERIAN GDP USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM DURING THE PERIOD 1990-2019

In this research, two different models, i.e. adaptive-network-based fuzzy inference system (ANFIS) and autoregressive integrated moving average (ARIMA) were used to predict the quarterly GDP in Algeria during the period 1990 to 2019. The comparison shows that the ANFIS1 model provides better accurac...

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Veröffentlicht in:Journal of Smart Economic Growth 2020-12, Vol.5 (2), p.11-21
Hauptverfasser: Abdelkader Sahed, Hacen Kahoui, Mohammed Mekidiche
Format: Artikel
Sprache:eng
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Zusammenfassung:In this research, two different models, i.e. adaptive-network-based fuzzy inference system (ANFIS) and autoregressive integrated moving average (ARIMA) were used to predict the quarterly GDP in Algeria during the period 1990 to 2019. The comparison shows that the ANFIS1 model provides better accuracy than the ARIMA(1,1,1) model in the quarterly forecast of GDP in Algeria. This is based on the quality prediction criterion of Root Mean Square Error (RMSE).
ISSN:2537-141X