Application of a Modified Statistical Segmentation Method to Timber Machine Strength Grading
Keywords:Timber, machine grading, statistics, classification
AbstractIn this paper, a new method for deriving grading rules is given. This method is based on the multiple regression and discrimination techniques by binary prediction trees, which are of high interest for classification purposes. A modification to the existing practice that tends to predict the bending modulus of rupture (MOR) is presented. This method consists in creating a nominal variable, the "optimal strength class value," which contains the information necessary to enter into a strength class system, i.e., the density, the bending modulus of elasticity (MOE), and the MOR. A comparison between a regression technique aimed at predicting the MOR and a discrimination technique aimed at predicting the optimal strength class assignment illustrates the innovative aspect of this method.
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