The use of an artificial neural network for predicting the gloss of thermally densified wood veneers

ÖZŞAHİN Ş., SİNGER H.

BALTIC FORESTRY, vol.27, no.2, pp.271-278, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 2
  • Publication Date: 2021
  • Doi Number: 10.46490/bf422
  • Journal Name: BALTIC FORESTRY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, Veterinary Science Database
  • Page Numbers: pp.271-278
  • Karadeniz Technical University Affiliated: Yes

Abstract

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 was employed for the development of the multilayer feed-forward ANN model. The wood species, temperature, pressure, measurement direction, and angle of incidence were considered as the model inputs, while the gloss was the output of the ANN model. Model performance was evaluated by using the mean absolute percentage error (MAPE), the root mean square error (RMSE), and the coefficient of determination (R-2). It was observed that the ANN model yielded very satisfactory results with acceptable deviations. The MAPE, RMSE, and R-2 values of the testing period of the ANN model were found as 8.556%, 1.245, and 0.9814, respectively. Consequently, this study could be useful for the wood industry to predict the gloss with a smaller number of labour consuming experimental activities.