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Forecasting Algerian Gdp Using Adaptive Neuro Fuzzy Inference System During The Period 1990-2019

Author

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  • Abdelkader Sahed

    (Faculty of Economics, University Centre of Maghnia, Maghnia, Algeria)

  • Hacen Kahoui

    (Faculty of Economics, University Centre of Maghnia, Maghnia, Algeria)

  • Mohammed Mekidiche

    (Faculty of Economics, University Centre of Maghnia, Maghnia, Algeria)

Abstract

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).

Suggested Citation

  • Abdelkader Sahed & Hacen Kahoui & Mohammed Mekidiche, 2020. "Forecasting Algerian Gdp Using Adaptive Neuro Fuzzy Inference System During The Period 1990-2019," Journal of Smart Economic Growth, , vol. 5(2), pages 11-21, September.
    • Handle: RePEc:seg:012016:v:5:y:2020:i:2:p:11-21
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    Keywords

    GDP; Forecasting; ANFIS; ARIMA; Algeria;
    All these keywords.

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