Abstract
This article focuses on forecasting the values added of agricultural sub-sectors, including agronomy, fishing,
forestry, animal husbandry and agricultural services, using the Artificial Neural Networks (ANN) model. It
compares the resulting figures with the target estimates throughout the plan [within the years 1384-1388 (2005-
2009)]. It turns out that the forecasted values added in the sub-sectors of agronomy and agricultural services are
higher and slower than the estimated values added required due to the plan, respectively. Also the high
conformity of the estimated and forecasted value added on the horizon of the fourth five-year plan, while the other
sub-sectors both the values are close to each other. The results indicate that the capability of ANN method for
forecasting variables is more suitable than the other methods.
