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| Registros recuperados : 84 | |
| 40. |  | LIMA, R. R.; CALZAVARA, B. B. G.; KITAMURA, P. C.; NASSAR, N. L. Histórico das atividades exercidas pelo IAN, IPEAN e EMBRAPA-CPATU no desenvolvimento da agropecuária na Amazônia. In: SIMPÓSIO SOBRE A HISTÓRIA DA CIÊNCIA E TECNOLOGIA NO PARÁ, 1985, Belém, PA. Anais... Belém, PA: UFPa, 1985. v. 2, p. 425-440.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| Registros recuperados : 84 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
14/05/2020 |
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Data da última atualização: |
27/08/2020 |
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Autoria: |
MARIANO, F. C. M. Q.; LIMA, R. R. de; ALVARENGA, R. R.; RODRIGUES, P. B. |
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Afiliação: |
Flávia Cristina Martins Queiroz Mariano, Universidade Federal de Lavras - UFLA/Departamento de Estatística; Renato Ribeiro de Lima, Universidade Federal de Lavras - UFLA/Departamento de Estatística; Renata Ribeiro Alvarenga, Universidade Federal de Lavras - UFLA/Departamento de Zootecnia; Paulo Borges Rodrigues, Universidade Federal de Lavras - UFLA/Departamento de Zootecnia. |
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Título: |
Committee neural network and weighted multiple regression to predict the energetic values of poultry feedstuffs. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, v. 55, e01199, 2020. |
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DOI: |
https://doi.org/10.1590/S1678-3921. pab2020.v55.01199. |
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Idioma: |
Inglês |
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Notas: |
Título em português: Comitê de redes neurais e regressão múltipla ponderada para a predição de valores energéticos de alimentos para aves de corte. |
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Conteúdo: |
The objective of this work was to compare the committee neural network (CNN) and weighted multiple linear regression (WMLR) models, in order to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of poultry feedstuffs. The prediction equation was adjusted by using a WMLR model and the meta-analysis principle. The models were compared by considering the correct prediction percentages, based on the classic prediction intervals and on the highest-probability density intervals, and by using a comparison test for proportions. The accuracy of the models was evaluated based on the values of the mean squared error, coefficient of determination, mean absolute deviation, mean absolute percentage error, and bias. Data from metabolic trials were used to compare the selected models. The committee neural network is the model that showed the highest accuracy of prediction, being recommended as the most accurate model to predict AMEn values for energetic concentrate feedstuffs used by the poultry feed industry. |
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Palavras-Chave: |
Broilers; Energia metabolizável; Highest-probability density interval; Intervalo de credibilidade da máxima probabilidade; Meta-análise; Percentage of success; Percentagem de acerto. |
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Thesagro: |
Frango de Corte. |
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Thesaurus NAL: |
Meta-analysis; Metabolizable energy. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/213017/1/Commitee-neural-network-and-weighted.pdf
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Marc: |
LEADER 02183naa a2200301 a 4500
001 2122326
005 2020-08-27
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/S1678-3921. pab2020.v55.01199.$2DOI
100 1 $aMARIANO, F. C. M. Q.
245 $aCommittee neural network and weighted multiple regression to predict the energetic values of poultry feedstuffs.$h[electronic resource]
260 $c2020
500 $aTítulo em português: Comitê de redes neurais e regressão múltipla ponderada para a predição de valores energéticos de alimentos para aves de corte.
520 $aThe objective of this work was to compare the committee neural network (CNN) and weighted multiple linear regression (WMLR) models, in order to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of poultry feedstuffs. The prediction equation was adjusted by using a WMLR model and the meta-analysis principle. The models were compared by considering the correct prediction percentages, based on the classic prediction intervals and on the highest-probability density intervals, and by using a comparison test for proportions. The accuracy of the models was evaluated based on the values of the mean squared error, coefficient of determination, mean absolute deviation, mean absolute percentage error, and bias. Data from metabolic trials were used to compare the selected models. The committee neural network is the model that showed the highest accuracy of prediction, being recommended as the most accurate model to predict AMEn values for energetic concentrate feedstuffs used by the poultry feed industry.
650 $aMeta-analysis
650 $aMetabolizable energy
650 $aFrango de Corte
653 $aBroilers
653 $aEnergia metabolizável
653 $aHighest-probability density interval
653 $aIntervalo de credibilidade da máxima probabilidade
653 $aMeta-análise
653 $aPercentage of success
653 $aPercentagem de acerto
700 1 $aLIMA, R. R. de
700 1 $aALVARENGA, R. R.
700 1 $aRODRIGUES, P. B.
773 $tPesquisa Agropecuária Brasileira$gv. 55, e01199, 2020.
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Embrapa Unidades Centrais (AI-SEDE) |
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