Abstract
The importance of increasing independence from oil revenues whatever the reason is, fluctuations in oil prices and global demand, government revenues severely affected and have led to the Euphrates secret tool exports to earn foreign currency to be raised. Hats why many experts and scholars of the current situation of the economy towards exports has shifted. Possible to examine the prospects for exports and provides more precise planning for the economy of Iran. This study evaluated the predictive power of Iran’s non-oil exports methods of Artificial Neural Network (ANN) and mass Autoregressive Moving Average (ARIMA) which was used. Required data for the years 1959 to 2010 were obtained from central bank of Iran. Therefore to compare the accuracy of prediction methods measure the average absolute deviation, root mean square error and coefficient of determination is used. The results showed that the artificial neural network techniques can also develop new methods of predicting and be a policy maker especially the non-oil export sector in decision-making in the future. The result seems to dollar exchange rate management policy in our country is a function of politics. Even if this rate is not always constant in long run.
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