Abstract In this study ARIMA and neural network auto-regressive methods for predicting retail product prices of tomatoes were Compared. The data were weekly that included the retail prices of tomatoes during 2009-2010 and gathered from Tehran fruits and vegetables organization. The results showed that non-linear neural network auto-regressive model, in predicting the retail price of tomatoes has a lower error and thus is more efficient than ARIMA.
Borimnejad, V., & Bakeshloo, M. (2013). Forecasting the Price of Tomatoes: Comparison of Syncretistic Methods of Neural Network Auto-Regressive and ARIMA. Agricultural Economics and Development, 21(3), 89-103. doi: 10.30490/aead.2013.58710
MLA
V. Borimnejad; M. Bakeshloo. "Forecasting the Price of Tomatoes: Comparison of Syncretistic Methods of Neural Network Auto-Regressive and ARIMA". Agricultural Economics and Development, 21, 3, 2013, 89-103. doi: 10.30490/aead.2013.58710
HARVARD
Borimnejad, V., Bakeshloo, M. (2013). 'Forecasting the Price of Tomatoes: Comparison of Syncretistic Methods of Neural Network Auto-Regressive and ARIMA', Agricultural Economics and Development, 21(3), pp. 89-103. doi: 10.30490/aead.2013.58710
VANCOUVER
Borimnejad, V., Bakeshloo, M. Forecasting the Price of Tomatoes: Comparison of Syncretistic Methods of Neural Network Auto-Regressive and ARIMA. Agricultural Economics and Development, 2013; 21(3): 89-103. doi: 10.30490/aead.2013.58710
)