Using artificial neural networks in estimating wood resistance

Abstract: The purpose of this research was to evaluate the potential of Artificial Neural Networks in estimating the properties of wood resistance. In order to do so, a hybrid of eucalyptus (Eucalyptus urograndis) planted in the Northern Region of the State of Mato Grosso was selected and ten trees...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Miguel,Eder Pereira, Melo,Rafael Rodolfo de, Serenini Junior,Laércio, Menezzi,Cláudio Henrique Soares Del
Lenguaje:	English
Publicado:	Universidad del Bío-Bío 2018
Materias:	Artificial intelligence Eucalyptus urograndis hardness mechanical properties non-destructive testing.
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000400531
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:scielo:S0718-221X2018000400531
record_format	dspace
spelling	oai:scielo:S0718-221X20180004005312019-02-14Using artificial neural networks in estimating wood resistanceMiguel,Eder PereiraMelo,Rafael Rodolfo deSerenini Junior,LaércioMenezzi,Cláudio Henrique Soares Del Artificial intelligence Eucalyptus urograndis hardness mechanical properties non-destructive testing. Abstract: The purpose of this research was to evaluate the potential of Artificial Neural Networks in estimating the properties of wood resistance. In order to do so, a hybrid of eucalyptus (Eucalyptus urograndis) planted in the Northern Region of the State of Mato Grosso was selected and ten trees were collected. Then, four samples of each tree were removed, totaling 40 samples, which were later subjected to non-destructive testing of apparent density, ultrasonic wave propagation velocity, dynamic modulus of elasticity obtained by ultrasound, and Janka hardness. These properties were used as estimators of resistance and compressive strength parallel to fibers, and hardness. Multilayer Perceptron networks were also employed, training 100 of them for each of the evaluated parameters. The obtained results indicated that the use of Artificial Neural Networks is an efficient tool for predicting wood resistance.info:eu-repo/semantics/openAccessUniversidad del Bío-BíoMaderas. Ciencia y tecnología v.20 n.4 20182018-10-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000400531en10.4067/S0718-221X2018005004101
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Artificial intelligence Eucalyptus urograndis hardness mechanical properties non-destructive testing.
spellingShingle	Artificial intelligence Eucalyptus urograndis hardness mechanical properties non-destructive testing. Miguel,Eder Pereira Melo,Rafael Rodolfo de Serenini Junior,Laércio Menezzi,Cláudio Henrique Soares Del Using artificial neural networks in estimating wood resistance
description	Abstract: The purpose of this research was to evaluate the potential of Artificial Neural Networks in estimating the properties of wood resistance. In order to do so, a hybrid of eucalyptus (Eucalyptus urograndis) planted in the Northern Region of the State of Mato Grosso was selected and ten trees were collected. Then, four samples of each tree were removed, totaling 40 samples, which were later subjected to non-destructive testing of apparent density, ultrasonic wave propagation velocity, dynamic modulus of elasticity obtained by ultrasound, and Janka hardness. These properties were used as estimators of resistance and compressive strength parallel to fibers, and hardness. Multilayer Perceptron networks were also employed, training 100 of them for each of the evaluated parameters. The obtained results indicated that the use of Artificial Neural Networks is an efficient tool for predicting wood resistance.
author	Miguel,Eder Pereira Melo,Rafael Rodolfo de Serenini Junior,Laércio Menezzi,Cláudio Henrique Soares Del
author_facet	Miguel,Eder Pereira Melo,Rafael Rodolfo de Serenini Junior,Laércio Menezzi,Cláudio Henrique Soares Del
author_sort	Miguel,Eder Pereira
title	Using artificial neural networks in estimating wood resistance
title_short	Using artificial neural networks in estimating wood resistance
title_full	Using artificial neural networks in estimating wood resistance
title_fullStr	Using artificial neural networks in estimating wood resistance
title_full_unstemmed	Using artificial neural networks in estimating wood resistance
title_sort	using artificial neural networks in estimating wood resistance
publisher	Universidad del Bío-Bío
publishDate	2018
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2018000400531
work_keys_str_mv	AT miguelederpereira usingartificialneuralnetworksinestimatingwoodresistance AT melorafaelrodolfode usingartificialneuralnetworksinestimatingwoodresistance AT sereninijuniorlaercio usingartificialneuralnetworksinestimatingwoodresistance AT menezziclaudiohenriquesoaresdel usingartificialneuralnetworksinestimatingwoodresistance
_version_	1714202660126588928

Using artificial neural networks in estimating wood resistance

Ejemplares similares