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:: Volume 15, Issue 44 (Winter 2008) ::
qjerp 2008, 15(44): 83-100 Back to browse issues page
Forecasting Rice and Corn Imports Using the Method of Artificial Neural Network
Mohammad Amin Shayegan, Hamid Mohammadi, Seyyed Nematollah Moosavi
Abstract:   (14934 Views)
The objective of this research work is to forecast the rice and corn imports using the methods of artificial neural network and ARIMA. The results are then compared. Calculations are based upon the data from the Iranian Customs regarding imports of rice and corn during the period 1360 to 1383. Data for the period 1360-1380 are used for educating the network, and data related to the last three years are used to examine the predictive power. The results show that the method of neural network has a better performance as compared to the process of ARIMA and is able to predict the rice and corn imports with higher accuracy.
Keywords: Imports, Rice, Corn, Artificial Neural Network
Full-Text [PDF 277 kb]   (1578 Downloads)    
Type of Study: Research | Subject: General
Received: 2012/09/5 | Published: 2008/01/15
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Shayegan M A, Mohammadi H, Moosavi S N. Forecasting Rice and Corn Imports Using the Method of Artificial Neural Network. qjerp. 2008; 15 (44) :83-100
URL: http://qjerp.ir/article-1-278-en.html


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Volume 15, Issue 44 (Winter 2008) Back to browse issues page
فصلنامه پژوهشها و سیاستهای اقتصادی Journal of Economic Research and Policies
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