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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
05/09/2018 |
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Data da última atualização: |
05/09/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
REIS, P. C. M. dos R.; SOUZA, A. L. de; REIS, L. P.; CARVALHO, A. M. M. L.; FREITAS, L. J. M. de; RÊGO, L. J. S.; LEITE, H. G. |
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Afiliação: |
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. |
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Título: |
Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Maderas. Ciencia y tecnología, v. 20, n. 3, p. 343-352, 2018. |
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DOI: |
10.4067/S0718-221X2018005003501 |
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Idioma: |
Inglês |
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Conteúdo: |
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. |
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Palavras-Chave: |
Inteligência artificial; Modelagem. |
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Thesagro: |
Madeira; Tecnologia. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/182447/1/0718-221X-maderas-03501.pdf
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Marc: |
LEADER 01851naa a2200253 a 4500
001 2095097
005 2018-09-05
008 2018 bl uuuu u00u1 u #d
024 7 $a10.4067/S0718-221X2018005003501$2DOI
100 1 $aREIS, P. C. M. dos R.
245 $aArtificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood.$h[electronic resource]
260 $c2018
520 $aTimber 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.
650 $aMadeira
650 $aTecnologia
653 $aInteligência artificial
653 $aModelagem
700 1 $aSOUZA, A. L. de
700 1 $aREIS, L. P.
700 1 $aCARVALHO, A. M. M. L.
700 1 $aFREITAS, L. J. M. de
700 1 $aRÊGO, L. J. S.
700 1 $aLEITE, H. G.
773 $tMaderas. Ciencia y tecnología$gv. 20, n. 3, p. 343-352, 2018.
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Registro original: |
Embrapa Amazônia Oriental (CPATU) |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
29/11/2013 |
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Data da última atualização: |
29/11/2013 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
ANDRADE, C. M. S. de; JANK, L.; FARINATTI, L. H. E.; NASCIMENTO, H. L. B. do. |
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Afiliação: |
CARLOS MAURICIO SOARES DE ANDRADE, CPAF-AC; LIANA JANK, CNPGC; LUIS H. E. FARINATTI, EMBRAPA ACRE; HEMYTHON L. B. DO NASCIMENTO, Federal University of Viçosa, Viçosa, MG. |
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Título: |
Nutritive value of Panicum maximum genotypes under grazing in the Amazon Biome. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
In: ANNUAL MEETING BRAZILIAN SOCIETY OF ANIMAL SCIENCE, 50., 2013, Campinas. The integration of Knowledge in animal production - abstracts. Campinas: SBZ, 2013 |
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Descrição Física: |
1 CD ROM |
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Idioma: |
Português |
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Palavras-Chave: |
Guineagrass; Plant fiber; Protein. |
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Thesagro: |
Silica. |
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Thesaurus NAL: |
digestibility; lignin. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/93337/1/LIANA-JANL-SBZ-2013-6GBJ.pdf
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Marc: |
LEADER 00736nam a2200217 a 4500
001 1972541
005 2013-11-29
008 2013 bl uuuu u00u1 u #d
100 1 $aANDRADE, C. M. S. de
245 $aNutritive value of Panicum maximum genotypes under grazing in the Amazon Biome.$h[electronic resource]
260 $aIn: ANNUAL MEETING BRAZILIAN SOCIETY OF ANIMAL SCIENCE, 50., 2013, Campinas. The integration of Knowledge in animal production - abstracts. Campinas: SBZ$c2013
300 $c1 CD ROM
650 $adigestibility
650 $alignin
650 $aSilica
653 $aGuineagrass
653 $aPlant fiber
653 $aProtein
700 1 $aJANK, L.
700 1 $aFARINATTI, L. H. E.
700 1 $aNASCIMENTO, H. L. B. do
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Registro original: |
Embrapa Gado de Corte (CNPGC) |
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