Comparison of NNARX, ANN and ARIMA Techniques to Poultry Retail Price Forecasting
AbstractThe lack of study among the economic forecasting literature that can empirically proves the hypothesis of being more powerfulness of dynamic neural networks in comparison with the static neural networks models for forecasting, is the most important motivation of this study. In this paper, the utilization of NNARX as a nonlinear dynamic neural network model, ANN as a nonlinear static neural network model and ARIMA as a linear model were compared to forecast poultry retail price. As a case study on Iranian poultry retail price, we compare forecast performance of these models for three forecasts (1, 2 and 4 week ahead). Results show that NNARX and ANN models outperform ARIMA model, and also NNARX model outperforms ANN model for all three forecasts.
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Bibliographic InfoPaper provided by International Association of Agricultural Economists in its series 2009 Conference, August 16-22, 2009, Beijing, China with number 50321.
Date of creation: 2009
Date of revision:
NNARX; Poultry Retail Price; Forecasting; Demand and Price Analysis; Marketing;
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