Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood

Abstract: Timber from the second cutting cycle may make up the majority of future crop volumetric. However, there are few studies of the physical and mechanical properties of this timber, which are important to support the consolidation of new species. This study aimed to use Artificial Neural Netwo...

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Autores principales:	Reis,Pamella Carolline Marques dos Reis, Souza,Agostinho Lopes de, Reis,Leonardo Pequeno, Carvalho,Ana Márcia Macedo Ladeira, Mazzei,Lucas, Rêgo,Lyvia Julienne Sousa, Leite,Helio Garcia
Lenguaje:	English
Publicado:	Universidad del Bío-Bío 2018
Materias:	Artificial intelligence modeling timber potential tropical wood wood technology
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000300343
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spelling	oai:scielo:S0718-221X20180003003432018-09-26Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle woodReis,Pamella Carolline Marques dos ReisSouza,Agostinho Lopes deReis,Leonardo PequenoCarvalho,Ana Márcia Macedo LadeiraMazzei,LucasRêgo,Lyvia Julienne SousaLeite,Helio Garcia Artificial intelligence modeling timber potential tropical wood wood technology Abstract: Timber from the second cutting cycle may make up the majority of future crop volumetric. However, there are few studies of the physical and mechanical properties of this timber, which are important to support the consolidation of new species. This study aimed to use Artificial Neural Networks to estimate the physical and mechanical properties of wood from the Amazon, based on basic density. The properties were: shrinkage (tangential, radial and volumetric), static bending, parallel and perpendicular to the fiber compression, parallel and transverse to the fibers, Janka hardness, traction, splitting and shear. The estimate followed the tendency of the data observed for the tangential, radial and volumetric shrinkage. The network estimated the mechanical properties with significant accuracy. Distribution of errors, static bending, parallel compression and perpendicular to the fiber compression also showed significant accuracy. Artificial Neural Networks can be used to estimate the physical and mechanical properties of wood from Amazon species.info:eu-repo/semantics/openAccessUniversidad del Bío-BíoMaderas. Ciencia y tecnología v.20 n.3 20182018-07-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000300343en10.4067/S0718-221X2018005003501
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Artificial intelligence modeling timber potential tropical wood wood technology
spellingShingle	Artificial intelligence modeling timber potential tropical wood wood technology Reis,Pamella Carolline Marques dos Reis Souza,Agostinho Lopes de Reis,Leonardo Pequeno Carvalho,Ana Márcia Macedo Ladeira Mazzei,Lucas Rêgo,Lyvia Julienne Sousa Leite,Helio Garcia Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
description	Abstract: Timber from the second cutting cycle may make up the majority of future crop volumetric. However, there are few studies of the physical and mechanical properties of this timber, which are important to support the consolidation of new species. This study aimed to use Artificial Neural Networks to estimate the physical and mechanical properties of wood from the Amazon, based on basic density. The properties were: shrinkage (tangential, radial and volumetric), static bending, parallel and perpendicular to the fiber compression, parallel and transverse to the fibers, Janka hardness, traction, splitting and shear. The estimate followed the tendency of the data observed for the tangential, radial and volumetric shrinkage. The network estimated the mechanical properties with significant accuracy. Distribution of errors, static bending, parallel compression and perpendicular to the fiber compression also showed significant accuracy. Artificial Neural Networks can be used to estimate the physical and mechanical properties of wood from Amazon species.
author	Reis,Pamella Carolline Marques dos Reis Souza,Agostinho Lopes de Reis,Leonardo Pequeno Carvalho,Ana Márcia Macedo Ladeira Mazzei,Lucas Rêgo,Lyvia Julienne Sousa Leite,Helio Garcia
author_facet	Reis,Pamella Carolline Marques dos Reis Souza,Agostinho Lopes de Reis,Leonardo Pequeno Carvalho,Ana Márcia Macedo Ladeira Mazzei,Lucas Rêgo,Lyvia Julienne Sousa Leite,Helio Garcia
author_sort	Reis,Pamella Carolline Marques dos Reis
title	Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
title_short	Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
title_full	Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
title_fullStr	Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
title_full_unstemmed	Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
title_sort	artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
publisher	Universidad del Bío-Bío
publishDate	2018
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000300343
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Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood

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