This paper aims to design an artificial neural network model to predict compression strength
parallel to grain of heat treated woods, without doing comprehensive experiments. In this …

The present study discusses about the effect of the aspect ratio of the fillers on the fracture
toughness of the glass-filled epoxy composites under impact loading. Three different kinds …

In this study, MOR and MOE of the heat-treated wood were predicted by artificial neural
networks (ANNs). For this purpose, samples were prepared from beech wood (Fagus …

The mechanical properties of bamboo-wood composites (BWC) remain crucial for potential
further employment. Nevertheless, the approach to detecting its mechanical properties is …

The optimum adjustment the CNC (Computer Numerical Control) processing parameters is
extremely important, especially in finishing processes such as coating, painting, and …

Determining the modulus of elasticity of wood by applying an artificial neural network using
the physical properties and non-destructive testing can be a useful method in assessments …

In this study, the hydration behavior of gypsum paste mixed with bagasse and kenaf fibers
as lignocellulosic material and fiberglass as inorganic material is evaluated. Moreover, the …

The structural application of plywood boards has increased considerably in recent years. In
this context, determining plywood mechanical properties such as bending strength and …

Efficient management of timber resources and wood utilization practices require accurate
and versatile information about important characteristics of forest resources for evaluating …

The purpose of this study was to predict the color change of heat-treated wood during
artificial weathering by an artificial neural network (ANN) model. Chemical component …