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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
16/08/2017 |
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Data da última atualização: |
07/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
DRURY, B.; VALVERDE-REBAZA, J.; MOURA, M. F.; LOPES, A. de A. |
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Afiliação: |
BRETT DRURY, ICMC/USP; JORGE VALVERDE-REBAZA, ICMC/USP; MARIA FERNANDA MOURA, CNPTIA; ALNEU DE ANDRADE LOPES, ICMC/USP. |
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Título: |
A survey of the applications of Bayesian networks in agriculture. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Engineering Applications of Artificial Intelligence, v. 65, p. 29-42, Oct. 2017. |
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DOI: |
https://doi.org/10.1016/j.engappai.2017.07.003 |
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Idioma: |
Inglês |
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Conteúdo: |
The application of machine learning to agriculture is currently experiencing a "surge of interest" from the academic community as well as practitioners from industry. This increased attention has produced a number of differing approaches that use varying machine learning frameworks. It is arguable that Bayesian Networks are particularly suited to agricultural research due to their ability to reason with incomplete information and incorporate new information. Bayesian Networks are currently underrepresented in the machine learning applied to agriculture research literature, and to date there are no survey papers that currently centralize the state of the art. The aim of this paper is rectify the lack of a survey paper in this area by providing a self-contained resource that will: centralize the current state of the art, document the historical progression of Bayesian Networks in agriculture and indicate possible future lines of research as well as providing an introduction to Bayesian Networks for researchers who are new to the area. |
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Palavras-Chave: |
Bayesian inference; Bayesian networks; Computational agriculture; Machine learning. |
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Thesagro: |
Agricultura. |
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Thesaurus Nal: |
Agriculture; Bayesian theory. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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024 7 $ahttps://doi.org/10.1016/j.engappai.2017.07.003$2DOI
100 1 $aDRURY, B.
245 $aA survey of the applications of Bayesian networks in agriculture.$h[electronic resource]
260 $c2017
520 $aThe application of machine learning to agriculture is currently experiencing a "surge of interest" from the academic community as well as practitioners from industry. This increased attention has produced a number of differing approaches that use varying machine learning frameworks. It is arguable that Bayesian Networks are particularly suited to agricultural research due to their ability to reason with incomplete information and incorporate new information. Bayesian Networks are currently underrepresented in the machine learning applied to agriculture research literature, and to date there are no survey papers that currently centralize the state of the art. The aim of this paper is rectify the lack of a survey paper in this area by providing a self-contained resource that will: centralize the current state of the art, document the historical progression of Bayesian Networks in agriculture and indicate possible future lines of research as well as providing an introduction to Bayesian Networks for researchers who are new to the area.
650 $aAgriculture
650 $aBayesian theory
650 $aAgricultura
653 $aBayesian inference
653 $aBayesian networks
653 $aComputational agriculture
653 $aMachine learning
700 1 $aVALVERDE-REBAZA, J.
700 1 $aMOURA, M. F.
700 1 $aLOPES, A. de A.
773 $tEngineering Applications of Artificial Intelligence$gv. 65, p. 29-42, Oct. 2017.
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Embrapa Agricultura Digital (CNPTIA) |
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| 4. |  | LEAL, L. K. A.; LOPES, A. de A.; ARARUNA, S. M.; VIANA, G. S. de B.; SILVEIRA, E. R.; CANUTO, K. M. Amburana cearensis (Fr. All.) A. C. Smith (cumaru). In: VIANA, G. S. B.; LEAL, L.K.A.M.; VASCONCELOS, S.M.M. (Org.). Plantas medicinais da caatinga: atividades biológicas e potencial terapêutico. Fortaleza: Expressão, 2013. p. 35-60| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Agroindústria Tropical. |
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| Registros recuperados : 4 | |
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