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Stručni rad

https://doi.org/10.5552/drind.2015.1434

Modeling of Compressive Strength Parallel to Grain of Heat Treated Scotch Pine (Pinus sylvestris L.) Wood by Using Artificial Neural Network

Fatih Yapıcı ; Fakultet inženjerstva, Odjel za industrijsko inženjerstvo, Samsun, Turska
Raşit Esen ; Sveučilište Karabük, Fakultet tehničkog obrazovanja, Odjel za namještaj i uređenje interijera, Karabük, Turska
Okan Erkaymaz ; Sveučilište Karabük, Fakultet tehničkog obrazovanja, Odjel za namještaj i uređenje interijera, Karabük, Turska
Hasan Baş ; Bülent Ecevit University, Engineering Faculty, Department of Computer Engineering, Zonguldak, Turkey


Puni tekst: engleski pdf 644 Kb

str. 347-352

preuzimanja: 959

citiraj


Sažetak

In this study, the compressive strength of heat treated Scotch Pine was modeled using artificial neural network. The compressive strength (CS) value parallel to grain was determined after exposing the wood to heat treatment at temperature of 130, 145, 160, 175, 190 and 205ºC for 3, 6, 9, 12 hours. The experimental data was evaluated by using multiple variance analysis. Secondly, the effect of heat treatment on the CS of samples was modeled by using artificial neural network (ANN).

Ključne riječi

wood; heat treatment; Artificial Neural Network; compressive strength

Hrčak ID:

150815

URI

https://hrcak.srce.hr/150815

Datum izdavanja:

7.1.2016.

Podaci na drugim jezicima: hrvatski

Posjeta: 2.223 *