Future projection and the sales of industrial wood in Turkey: artificial neural networks


Abstract: In this study, it was aimed to determine artificial neural network models with different architectures using artificial neural network (ANN) methods used in future prediction studies in recent times and forecast the sales quantities of industrial wood in Turkey with the help of models. The sales quantities of logs, mining poles, other industrial wood, pulpwood, fiber-chip wood, and the total of these five wood groups were analyzed separately. The data used in this study was obtained from the General Directorate of Forestry of Turkey and cumulative monthly data covering the period from January 2001 to December 2016 were used. The most suitable ANN models were determined using performance criteria such as mean absolute percentage error (MAPE), root mean square error (RMSE), and determination coefficient (R2). As a result, the R2 and MAPE values of the ANN models were found to be above 99% and below 6%, respectively. The ANNs can be used as a good tool in industrial wood sales forecasts.

Keywords: Sale of industrial wood, forecasting, artificial neural networks

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