Modeling and comparison of bonding strength of impregnated wood material by using different methods: Artifıcial neural network and multiple linear regression
Yükleniyor...
Dosyalar
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Slovak Forest Products Research Inst
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, the effects of vacuum time, diffusion time and pressing time on the bonding strength of Larix decidua wood impregnated with Immersol-Aqua and bonded with Klebit-303 were investigated. The vacuum time, diffusion time, and pressing time were predicted by using the artificial neural network (ANN) model and multiple linear regression (MLR) methods and the results of ANN and MLR methods were compared. The highest bonding strength (7.664 N.mm(-2)) was achieved when the vacuum time, the diffusion time and the pressing time were 20, 60 and 60 minutes, respectively, while the lowest value (4.62 N.mm(-2)) was achieved when the vacuum time, the diffusion time and the pressing time were 80, 120 and 20 minutes, respectively. The model results are as follows: The MAPE value for testing phase in the ANN was 7.266 and R-2 value was 0.751 whereas the MAPE value of the MLR was 9.365 and R-2 value was 0.558. The ANN model has been found to have better prediction performance than the MLR model.
Açıklama
Research was carried out under development project (No: 2016. F90.02.05), financed by Artvin Coruh University Scientific Research Project Coordinator.
Anahtar Kelimeler
Artificial neural network, MLR, Bonding strength, Impregnation
Kaynak
Wood Research
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
64
Sayı
3
Künye
Akyüz, I., Ersen, N., Tiryaki, S., Bayram, B. Ç., Akyüz, K. C., & Peker, H. (2019). Modeling and comparison of bonding strength of impregnated wood material by using different methods: Artifıcial neural network and multiple linear regression, 64(3), 483-498.
