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

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dc.creatorPamella Carolline Reis Marques dos Reis
dc.creatorAgostinho Lopes de Souza
dc.creatorLeonardo Pequeno Reis
dc.creatorAna Márcia Macedo Ladeira Carvalho
dc.creatorLucas Mazzei
dc.creatorLyvia Julienne Sousa Rêgo
dc.creatorHelio Garcia Leite
dc.date2018
dc.date.accessioned2026-07-07T04:37:29Z
dc.descriptionTimber 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.
dc.formatapplication/pdf
dc.identifier0717-3644
dc.identifierhttps://www.redalyc.org/articulo.oa?id=48557683005
dc.identifierhttps://www.redalyc.org/journal/485/48557683005/
dc.identifierhttps://www.redalyc.org/journal/485/48557683005/html/
dc.identifierhttps://www.redalyc.org/journal/485/48557683005/48557683005.epub
dc.identifierhttps://www.redalyc.org/journal/485/48557683005/movil
dc.identifier.urihttp://hdl.handle.net/123456789/467310
dc.languageen
dc.publisherUniversidad del Bío Bío
dc.relationhttp://www.redalyc.org/revista.oa?id=485
dc.rightsMaderas. Ciencia y Tecnología
dc.sourceMaderas. Ciencia y Tecnología (Chile) Num.3 Vol.20
dc.subjectAgrociencias
dc.titleArtificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
dc.typeartículo científico

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Maderas. Ciencia y Tecnología - Universidad del Bío Bío