Files
Abstract
In the present study Iran's rice imports trend is forecasted,
using artificial neural networks and econometric methods,
during 2009 to 2013, and their results are compared. The
results showed that feet forward neural network leading with
less forecast error and had better performance in comparison
to econometric techniques and also, other methods of neural
networks, such as Recurrent networks and Multilayer perceptron
networks. Moreover, the results showed that the amount of
rice import has ascending growth rate in 2009-2013 and
maximum growth occurs in 2009-2010 years, which was equal
to 25.72 percent. Increasing rice import caused a lot of exchange
to exit out of the country and also, irreparable damage in
domestic production, both in terms of price and quantity. Considering
mentioned conditions, economic policy makers should
seek ways to reduce increasing trend of rice import; and more
investment and planning for domestic rice producers.