3 research outputs found
PREDICTING CONE PRODUCTION IN CLONAL SEED ORCHARD OF ANATOLIAN BLACK PINE WITH ARTIFICIAL NEURAL NETWORK
PREDICTING CONE PRODUCTION IN CLONAL SEED ORCHARD OF ANATOLIAN BLACK PINE WITH ARTIFICIAL NEURAL NETWORK
PREDICTING CONE PRODUCTION IN CLONAL SEED ORCHARD OF ANATOLIAN BLACK PINE WITH ARTIFICIAL NEURAL NETWORK
Seed orchards are an important seed source because they have the most
important link between tree breeding and plantation forestry. The aim of
this study is to evaluate the potential of Adaptive Neuro - Fuzzy
Inference Systems of artificial neural networks to predict the amount of
cone in clonal seed orchards of Anatolian black pine. It was found that
the coefficient of determination (R 2 ), the mean absolute error (MAE)
and the root mean square error (RMSE) of the artificial neural network
model were 0.85, 14.83 and 18.85, respectively. The amount of cone in
clonal seed orchards of Anatolian black pine was predicted with high
efficiency through artificial neural networks. Considering the lack of
forestry studies based on the artificial neural network, this study will
enable further researches to provide a new perspective