Trend of product point of wood and paper products is showing economic status of wood and paper industry and future situation prediction of these products is essential. Two methods of Artificial Neural Networks (ANN) and Autoregressive integrated moving average (ARIMA) were compared and monthly product point was forecasted for 2011. Performance evaluation criteria and MAPE was measured. Our results show that MAPE is low, especially in the ARIMA method, but predicted inflation rate of ARIMA is the same of past periods (2002 to 2010) and also, predicted inflation rate of ANN is similar to target periods. Approximately, the same product point is predicted by both methods and product point will increase, inconsequentially. But the monthly time series data of both product points are non stationary from 2002 to 2010. So probably, economics shocks as the subsidies scheme will affect product point and this subject will cause of upward product point.
keikha, A., & Rafighi, A. (2014). Comparing of product point forecasting of paper and wood products of Iran by methods of ANN and ARIMA. Journal of Wood and Forest Science and Technology, 21(2), 15-30.
MLA
Alireza keikha; Ali Rafighi. "Comparing of product point forecasting of paper and wood products of Iran by methods of ANN and ARIMA". Journal of Wood and Forest Science and Technology, 21, 2, 2014, 15-30.
HARVARD
keikha, A., Rafighi, A. (2014). 'Comparing of product point forecasting of paper and wood products of Iran by methods of ANN and ARIMA', Journal of Wood and Forest Science and Technology, 21(2), pp. 15-30.
VANCOUVER
keikha, A., Rafighi, A. Comparing of product point forecasting of paper and wood products of Iran by methods of ANN and ARIMA. Journal of Wood and Forest Science and Technology, 2014; 21(2): 15-30.
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