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 neuralnetwork (ANN) methods used in future prediction studies in recent times and forecast the sales quantities of industrial wood in Turkeywith the help of models. The sales quantities of logs, mining poles, other industrial wood, pulpwood, fiber-chip wood, and the total ofthese five wood groups were analyzed separately. The data used in this study was obtained from the General Directorate of Forestryof Turkey and cumulative monthly data covering the period from January 2001 to December 2016 were used. The most suitable ANNmodels 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.