Recursive diameter prediction and volume calculation of eucalyptus trees using Multilayer Perceptron Networks

被引:44
作者
Soares, Fabrizzio Alphonsus A. M. N. [1 ]
Flores, Edna Lucia [2 ]
Cabacinha, Christian Dias [3 ]
Carrijo, Gilberto Arantes [2 ]
Paschoarelli Veiga, Antonio Claudio [2 ]
机构
[1] Univ Fed Goias, Inst Informat, Goiania, Go, Brazil
[2] Univ Fed Uberlandia, Fac Elect Engn, Uberlandia, MG, Brazil
[3] Univ Fed Minas Gerais, Inst Ciencias Agr, Belo Horizonte, MG, Brazil
关键词
Estimating diameter; Forest inventory; Multilayer Perceptron; Recursive prediction; Volumetric equations;
D O I
10.1016/j.compag.2011.05.008
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
A major challenge in forest management is the ability to quickly and accurately predict bole volume of standing trees. This study presents a new model that uses Multilayer Perceptron (MLP) artificial neural networks for predicting tree diameters values. The model requires three diameter measures at the base of the tree, and recursively predicts other diameter measures. The predicted diameters allow for calculating tree volume using the Smalian method. The performance of the proposed model was satisfactory when compared with data obtained from tree scaling and volume equations. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:19 / 27
页数:9
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