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1. | | DORNELES JUNIOR, J.; ALMEIDA, G. R. de; ZANOTTA, S.; DOLCEMASCOLLO, T. P.; PEREIRA, L. S.; APOLINÁRIO, M. L.; PRADO, S. de S. Levantamento populacional de cigarrinhas, potenciais vetoras de Xylella fastidiosa, sob condições de aumento de dióxido de carbono em plantas de café. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 49., 2016, Maceió. Anais... Maceió: Sociedade Brasileira de Fitopatologia, 2016. Ref. 632. Biblioteca(s): Embrapa Meio Ambiente. |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pecuária Sul. |
Data corrente: |
09/01/2018 |
Data da última atualização: |
07/01/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 4 |
Autoria: |
FERREIRA, L. M.; SILVA, J. de A.; SANT'ANA, G. C.; CANÇADO, G. M. de A.; BORÉM, A.; FERREIRA, J. L. |
Afiliação: |
LEILA MARIA FERREIRA, Ufla; JANAÍNA DE ANDRADE SILVA, UFJF; GUSTAVO CÉSAR SANT’ANA, Agronomic Research for Development, France; GERALDO MAGELA DE ALMEIDA CANCADO, CNPTIA; ALUÍZIO BORÉM, UFV; JULIANO LINO FERREIRA, CPPSUL. |
Título: |
Application of artificial neural networks in the simulation with genetic data. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
International Journal of Engineering Inventions, v. 6, n. 12, p. 43-46, Dec. 2017. |
Idioma: |
Inglês |
Conteúdo: |
Abstract: The objective of this work was the concept of applying artificial neural networks in the study of genetic data, in order to make the identification of the microsatellite markers for a particular species of plant to be analyzed more efficient. In this study, was used as an experimental model the data generated for 26 grapevine genotypes were divided into the following populations: Vitis vinifera; North American varieties; and intersp ecific hybrid of rootstocks. After the network training was carried out, an error rate of 0.0003460 was obtained, concluding that the network was able to learn according to the type of data used, even when these data are small. |
Palavras-Chave: |
Grapevine; Network; Redes neurais. |
Thesagro: |
Genética; Genótipo. |
Thesaurus NAL: |
Genotype; Neural networks. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 01433naa a2200265 a 4500 001 2084780 005 2020-01-07 008 2017 bl uuuu u00u1 u #d 100 1 $aFERREIRA, L. M. 245 $aApplication of artificial neural networks in the simulation with genetic data.$h[electronic resource] 260 $c2017 520 $aAbstract: The objective of this work was the concept of applying artificial neural networks in the study of genetic data, in order to make the identification of the microsatellite markers for a particular species of plant to be analyzed more efficient. In this study, was used as an experimental model the data generated for 26 grapevine genotypes were divided into the following populations: Vitis vinifera; North American varieties; and intersp ecific hybrid of rootstocks. After the network training was carried out, an error rate of 0.0003460 was obtained, concluding that the network was able to learn according to the type of data used, even when these data are small. 650 $aGenotype 650 $aNeural networks 650 $aGenética 650 $aGenótipo 653 $aGrapevine 653 $aNetwork 653 $aRedes neurais 700 1 $aSILVA, J. de A. 700 1 $aSANT'ANA, G. C. 700 1 $aCANÇADO, G. M. de A. 700 1 $aBORÉM, A. 700 1 $aFERREIRA, J. L. 773 $tInternational Journal of Engineering Inventions$gv. 6, n. 12, p. 43-46, Dec. 2017.
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Embrapa Agricultura Digital (CNPTIA) |
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