Multilayer Percepton for Recursive Diameter Prediction of Eucalyptus Clones

Abstract

A major challenge in the forest area is the prediction of the volume of forest stands quickly and accurately without the need to fell trees. The purpose of this work is a model that uses artificial neural network Multilayer Perceptron (MLP) for predicting tree diameters. This model requires three measurements of diameter of the base of the tree and recursively provides other measures of diameters. The performance of the proposed model was satisfactory when compared with diameters obtained from the cubed.

Publication
In Proceedings of 10th Brazilian Symposium on Intelligent Automation (SBAI)

Text in Portuguese, Original Title: Multi-Layer perceptron na predicao recursiva de Diametros de clone de eucalipto.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.

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