Use of Artificial Neural Network (ANN) and Time Series Approach for Prediction of Electricity consumption in Agricultural sector

Author

• M. Ebrahimi

Abstract

The main object of this study is to predict electricity consumption of agricultural sector in Iran. To get the objective, time series method of Auto-Regressive Moving Average (ARMA) and artificial neural networks (ANN) were used. Annual data for period of 1967 to 2008 was used. The Mean Absolute Percent Error (MAPE), Root of Mean of Squared Error (RMSE) and Mean Absolute Error (MAE) criteria were used for comparing the ability of different forecasting methods. As the result showed Feed Forward artificial neural network with back proportion algorithm can predict electricity consumption with MAPE equal to 1.02%, while the corresponding value for time series model obtained 1.13 percent. Other criteria also revealed the same result, so, ANN is expected to predict electricity consumption more precise than ARMA model. Therefore, energy ministry may use ANN in future predictions.
 

Keywords

• Prediction
• energy consumption
• Artificial neural network
• Agricultural Sector

20.1001.1.20086407.1391.4.13.2.2

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