ISSN: 2222-6990
Open access
An analysis of the effects of various factors such as climate factors on wheat yield was performed in
Iran country in order to obtain models suitable for yield estimation and regional grain production
prediction. Climate data from meteorological records and other data from central bank of Iran were
employed. Annual data for 18 years were applied in this study. In order to predict wheat production,
artificial neural networks (ANN) methodologies were tested for analyzing the data. To conduct this
review, we have considered 8 factors as inputs and wheat production is used as output for the ANN
algorithm. Our input variables are: rainfall, guaranteed purchasing price, area under cultivation,
subsidy, insured area, inventory, import, population, value-added of agriculture group. The comparison
of real wheat production with ANN output in the last five years of this study shows that the proposed
ANN model is a suitable way of predicting wheat production.
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