The use of an artificial neural network for predicting the gloss of thermally densified wood veneers
Yükleniyor...
Dosyalar
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inst Forestry Lrcaf
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Artificial Neural Network, Gloss, Prediction, Veneer, Wood, Surface-Roughness
Kaynak
Baltic Forestry
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
27
Sayı
2
Künye
Özşahin, Ş., & Singer, H. (2021). The use of an artificial neural network for predicting the gloss of thermally densified wood veneers. Baltic Forestry, 27(2).
