Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood
| Autor: | Lyvia Julienne Sousa Rêgo, Agostinho Lopes de Souza, Helio Garcia Leite, Ana Márcia Macedo Ladeira Carvalho, Pamella Carolline Marques dos Reis Reis, Lucas Mazzei, Leonardo Pequeno Reis |
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| Přispěvatelé: | Pamella Carolline Marques dos Reis Reis, UFV, Agostinho Lopes de Souza, UFV, Leonardo Pequeno Reis, Instituto de Desenvolvimento Sustentável Mamirauá, Ana Márcia Macedo Ladeira Carvalho, UFV, LUCAS JOSE MAZZEI DE FREITAS, CPATU, Lyvia Julienne Sousa Rêgo, UFV, Helio Garcia Leite, UFV. |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Artificial intelligence
Materials science Materials Science (miscellaneous) Industrial and Manufacturing Engineering Parallel compression Madeira lcsh:Manufactures Perpendicular Chemical Engineering (miscellaneous) timber potential lcsh:Forestry Shrinkage 040101 forestry Consolidation (soil) Artificial neural network business.industry Forestry modeling 04 agricultural and veterinary sciences Structural engineering Inteligência artificial artificial intelligence tropical wood Transverse plane Cutting cycle Tecnologia 040103 agronomy & agriculture Basic density 0401 agriculture forestry and fisheries lcsh:SD1-669.5 business Modelagem wood technology lcsh:TS1-2301 |
| Zdroj: | Maderas: Ciencia y Tecnología, Vol 20, Iss 3, Pp 343-352 (2018) Maderas. Ciencia y tecnología v.20 n.3 2018 SciELO Chile CONICYT Chile instacron:CONICYT Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice) Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA Maderas. Ciencia y tecnología, Volume: 20, Issue: 3, Pages: 343-352, Published: JUL 2018 |
| ISSN: | 0717-3644 0718-221X |
| Popis: | 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. Made available in DSpace on 2018-09-06T00:32:52Z (GMT). No. of bitstreams: 1 0718221Xmaderas03501.pdf: 763544 bytes, checksum: 2c2ecbf501a1084501cca89f0a0723af (MD5) Previous issue date: 2018-09-05 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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