Prediction of Modulus of Rupture and Modulus of Elasticity of Heat Treated Anatolian Chestnut (Castanea Sativa) Wood by Fuzzy Logic Classifier

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Yapici F., Ulucan D.

DRVNA INDUSTRIJA, cilt.63, ss.37-43, 2012 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 63 Konu: 1
  • Basım Tarihi: 2012
  • Doi Numarası: 10.5552/drind.2012.1135
  • Sayfa Sayıları: ss.37-43


In this study test samples prepared from Anatolian chestnut (Castanea saliva) wood were first exposed to heat treatment at 130, 145, 160, 175, 190 and 205 degrees C for 3, 6, 9 and 12 hours. Then the values of the samples of the modulus of rupture (MOR) and modulus of elasticity (MOE) were determined and evaluated by multiple variance analysis. The aim of this study was to establish the effects of heat treatment on the MOR and MOE values of wood samples by using fuzzy logic classifier Secondly, input and output values and rule base of the fuzzy logic classifier model were built by using the results obtained from the experiment. The developed fuzzy classifier model could predict the MOR and MOE values of test samples at the accuracy levels of 92.64 % and 90.35 %, respectively The model could be especially employed in manufacturing stages of timber industry