Modeling and Predicting Agricultural Energy Consumption in Iran

Abstract: According to economical theories and views, energy is one of the main and the most important production factors in agricultural section. Predicting its future consumption is an important step in macro-planning in agricultural and energy sections. To predict energy consumption in future in Iran agricultural section, time series models and artificial neural networks were used and the results were compared. To carry out the reviews, information of the time period of 1976-2001 was used for modeling and of 2002-2007 was used to compare the predictive power of these two mentioned methods. Results revealed that artificial neural networks had a better prediction in comparison with ARIMA model. Then, the annual energy consumption in agricultural section was predicted by neural networks for time period of 2008-2011