Araucaria Stem Taper or Use of Artificial Intelligence Techniques

ABSTRACT The aim of this study was to compare the performance of artificial intelligence techniques with taper functions and evaluate the effect of age on this estimate. The data set was comprised of 135 observations covering the ages 6, 12, 18, 24 and 43 years of age of a stand of Araucaria angustifolia. Adjusted taper functions were Kozak Schöepfer, Hradetzky and Garay modified. The artificial intelligence models used were: ANN and tree model. The input vectors are the same variables used in taper equations and also the same arrangement with the addition of age. 70% of the data was used for adjustment and 30% for validation. The taper function Hradetzky provided the best fit. Among the models evaluated, the ANN provided the best estimates, highlighting the ANN by adding the age variable. The performance of M5P was satisfactory, however, less effective than the other techniques.