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Predicting Power Consumption using Algorithm of artificial Neural networks; Case Study: Golestan Province

Author Affiliations

  • 1 Islamic Azad University of Firouzkouh branch, Tehran, IRAN

Res. J. Recent Sci., Volume 4, Issue (6), Pages 7-12, June,2 (2015)


Today, using smart technologies for solving complex scientific problems in different industrial sectors have been significantly considered. The systems could achieve general facts through conducting calculations on empirical data. Hence, the systems can be called intelligent systems. Neural networks are kinds of these intelligent systems, which can transfer hidden knowledge beyond the data to structure of network through processing empirical data. The main objective of the present study is predicting power consumption using algorithm of artificial neural networks, which would be done as case study in Golestan province Iran. Generally, in order to predict future events, historical events and data would be considered. For this purpose, previous data would be processed, so that a generalized pattern for future can be achieved. In most methods of prediction, one can assume that relations among variables would be continued even in future. Information and data about demand for power consumption in each period is an essential issue in order to have exact planning and proper policy making. Hence, prediction of power consumption would be significant for different economic units. Obtained results from the study indicate that feed-forward neural network model has high validity level, comparing to routine prediction models for power consumption.


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