The Use of an Artificial Neural Network for Predicting the Gloss of Thermally Densified Wood Veneers

In this study, an artificial neural network (ANN) model was developed to predict the gloss of thermally densified wood veneers. A custom application created with MATLAB codes employed for development multilayer feed-forward ANN model. The species, temperature, pressure, measurement direction, and angle incidence were considered as inputs, while output Model performance evaluated by using mean absolute percentage error (MAPE), root square (RMSE), coefficient determination (R²). It observed that yielded very satisfactory results acceptable deviations. MAPE, RMSE, R2 values testing period found 8.556%, 1.245, 0.9814, respectively. Consequently, study could be useful industry less number tiring experimental activities.