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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
18/09/2014 |
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Data da última atualização: |
02/06/2017 |
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Autoria: |
FERRAZ, P. F. P.; YANAGI JUNIOR, T.; HERNÁNDEZ JULIO, Y. F.; CASTRO, J. de O.; GATES, R. S.; REIS, G. M.; CAMPOS, A. T. |
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Afiliação: |
PATRICIA FERREIRA PONCIANO FERRAZ, UFLA; TADAYUKI YANAGI JUNIOR, UFLA; FABIÁN HERNÁNDEZ JULIO, UFLA; JAQUELINE DE OLIVEIRA CASTRO, UFLA; RICHARD STEPHEN GATES, University of Illinois; GREGORY MURAD REIS, UFLA; ALESSANDRO TORRES CAMPOS, UFLA. |
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Título: |
Predicting chick body mass by artificial intelligence-based models. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 7, p. 559-568, jul. 2014. |
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Idioma: |
Inglês |
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Notas: |
Título em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial. |
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Conteúdo: |
The objective of this work was to develop, validate, and compare 190 artificial intelligence‑based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside our climate‑controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21‑day‑old hicks) ? with the variables dry‑bulb air temperature, duration of thermal stress (days), chick ageb (days), and the daily body mass of chicks ? was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro‑fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The NNs enable the simulation of different scenarios, which can assist in managerial decision‑making, and they can be embedded in the heating control system. |
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Palavras-Chave: |
Artificial neural networks; Modeling; Neuro-fuzzy network; Thermal comfort. |
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Thesaurus Nal: |
Animal welfare. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/108680/1/Predicting-chick-body.pdf
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Marc: |
LEADER 01954naa a2200265 a 4500
001 1995322
005 2017-06-02
008 2014 bl uuuu u00u1 u #d
100 1 $aFERRAZ, P. F. P.
245 $aPredicting chick body mass by artificial intelligence-based models.
260 $c2014
500 $aTítulo em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial.
520 $aThe objective of this work was to develop, validate, and compare 190 artificial intelligence‑based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside our climate‑controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21‑day‑old hicks) ? with the variables dry‑bulb air temperature, duration of thermal stress (days), chick ageb (days), and the daily body mass of chicks ? was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro‑fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The NNs enable the simulation of different scenarios, which can assist in managerial decision‑making, and they can be embedded in the heating control system.
650 $aAnimal welfare
653 $aArtificial neural networks
653 $aModeling
653 $aNeuro-fuzzy network
653 $aThermal comfort
700 1 $aYANAGI JUNIOR, T.
700 1 $aHERNÁNDEZ JULIO, Y. F.
700 1 $aCASTRO, J. de O.
700 1 $aGATES, R. S.
700 1 $aREIS, G. M.
700 1 $aCAMPOS, A. T.
773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 49, n. 7, p. 559-568, jul. 2014.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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| Registros recuperados : 2 | |
| 1. |  | FERRAZ, P. F. P.; YANAGI JUNIOR, T.; LIMA, R. R. de; FERRAZ, G. A. e S.; XIN, H. Performance of chicks subjected to thermal challenge. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 52, n. 2, p. 113-120, fev. 2017. Título em português: Desempenho de pintinhos submetidos a estresse térmico.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 2. | | FERRAZ, P. F. P.; YANAGI JUNIOR, T.; HERNÁNDEZ JULIO, Y. F.; CASTRO, J. de O.; GATES, R. S.; REIS, G. M.; CAMPOS, A. T. Predicting chick body mass by artificial intelligence-based models. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 7, p. 559-568, jul. 2014. Título em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial.| Biblioteca(s): Embrapa Unidades Centrais. |
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| Registros recuperados : 2 | |
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