Multilayer Percepton for Recursive Diameter Prediction of Eucalyptus Clones

Multilayer Percepton for Recursive Diameter Prediction of Eucalyptus Clones

Abstract

A major challenge in forest management is the ability to quickly and accurately predict bole volume of standing trees. This study presents a model that uses Multilayer Perceptron (MLP) artificial neural networks for predicting tree volume. The model requires three diameter measures at the base of the tree, and recursively predicts other diameter measures. The performance of the proposed model was satisfactory when compared with data obtained from tree scaling.

Publication
In Proceedings of 8th UFU Conference on Electrical Engineering Studies (CEEL)
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Text in Portuguese, Original Title: Multi-Layer perceptron na predicao recursiva de Diametros de clone de eucalipto.