DIGITALNA ARHIVA ŠUMARSKOG LISTA
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| ŠUMARSKI LIST 9-10/2019 str. 38 <-- 38 --> PDF |
the t-paired test evaluating null hypothesis of a mean prediction residual equal to zero including validation data set, 54 sample trees. The results for t-paired test show that the mean residuals predicted from ANN based on MLP 1-9-1 for single-entry volume predictions are not significantly different from zero, t value=-0.364, p=0.718>0.05. Also, the mean residuals predicted from ANN MLP 2-15-1 for double-entry volume predictions are not significantly different from zero, t value=0.559, p=0.578>0.05 Discussion Rasprava In this study, it was aimed to obtain the individual volume predictions of Crimean Black Pine in Çankırı Forests by using Artificial Neural Network Models. Also, the single and double entry-volume equations and the Fang et al. (2000)’s compatible volume equation based on the classical and traditional methods were used to acquire these tree volume predictions. The single-entry volume equation accounted for about 90.82 % of the total variance in volume predictions, however, the best predictive ANN based on MLP 1-9-1 and ANN based on RBF 1-7-1 presented about 93.37 % and 91.57 % of explanatory at the total variance of volume predictions, respectively. To include dbh and height as independent in tree volume predictions, the double-entry volume equations and the Fang (2000)’s compatible volume equation accounted for about 95.17 % and 91.73 % of the total variance in volume predictions, respectively. The ANN-based on MLP 2-15-1 and ANN based on RBF 2-9-1 including dbh and height as input variables presented the best predictive results including about 98.01 % and 93.73 % of the total variance in volume predictions, respectively. The principal purpose of this study was to reveal the usability of prediction methods based on the Artificial Neural |