Data/hora: 13/06/2024 02:14:15

Provedor de dados: 	190	
País: 	Brazil	
Título: 	Estimate of Acacia mangium volume using techniques of artificial neural networks and support vector machines

Estimativa do volume de Acacia mangium utilizando técnicas de redes neurais artificiais e máquinas vetor de suporte	
Autores: 	Cordeiro, Márcio Assis; Pereira, Nayara Natacha de Jesus; Binoti, Daniel Henrique Breda; Binoti, Mayra Luiza Marques da Silva; Leite, Hélio Garcia.	
Data: 	2015-09-30	
Ano: 	2015	
Palavras-chave: 	Smalian; Modeling; Volumetric estimates Engenharia Florestal Manejo Florestal Recursos Florestais Smalian; Modelagem; Estimativa volumétrica.	
Resumo: 	The present study aimed to show the results of Acacia mangium volumetric estimates obtained through the Schumacher and Hall model compared to the methods of artificial neural networks and support vector machines. To enable this comparative analysis, we used data from 31 trees of Acacia mangium aged 14–17, from a stand located in the northern region of the state of Amapá. Diameter and bark thickness of the trees were measured into relative heights along the stem into 14 sections (0.05%, 1%, 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 95%), with measurement. Total volume with bark was obtained by applying the Smalian formula. In general, the methods that differ from traditional methods showed statistically superior results.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Português	
Identificador: 	http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/596

10.4336/2015.pfb.35.83.596	
Editor: 	Embrapa Florestas	
Relação: 	http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/596/433	
Formato: 	application/pdf	
Fonte: 	Brazilian Journal of Forestry Research; v. 35, n. 83 (2015): jul./set.; 255-261

Pesquisa Florestal Brasileira; v. 35, n. 83 (2015): jul./set.; 255-261

1983-2605

1809-3647	
Fonte: 	Direitos autorais 2015 Pesquisa Florestal Brasileira

http://creativecommons.org/licenses/by-nc-nd/4.0