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British Poultry Science Volume 44, 2003 - Issue 2
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Original Articles

Use of artificial neural networks to estimate production variables of broilers breeders in the production phase

C.T.P. Salle Faculty of Veterinary Medicine, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
,
A.S. Guahyba Ministry of Agriculture Livestock and Food Supply, Brazilian Government, Brasilia, DF, Brazil
,
V.B. Wald Faculty of Veterinary Medicine, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
,
A.B. Silva Faculty of Veterinary Medicine, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
,
F.O. Salle Vale dos Sinos University (UNISINOS), São Leopoldo, RS, Brazil
&
V.P. Nascimento Faculty of Veterinary Medicine, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
Pages 211-217 | Published online: 28 Jun 2010

Citations (14)

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Read on this site (1)

H. Ahmadi, M. Mottaghitalab, N. Nariman-Zadeh & A. Golian. (2008) Predicting performance of broiler chickens from dietary nutrients using group method of data handling-type neural networks. British Poultry Science 49:3, pages 315-320.
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Articles from other publishers (13)

Elisar Camilotti, Thales Quedi Furian, Karen Apellanis Borges, Daniela Tonini da Rocha, Vladimir Pinheiro do Nascimento, Hamilton Luiz de Souza Moraes & Carlos Tadeu Pippi Salle. (2023) Redes neurais artificiais para o gerenciamento da indústria avícola: uma simulação baseada na cadeia de produção de frangos de corte. Ciência Animal Brasileira 24.
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Elisar Camilotti, Thales Quedi Furian, Karen Apellanis Borges, Daniela Tonini da Rocha, Vladimir Pinheiro do Nascimento, Hamilton Luiz de Souza Moraes & Carlos Tadeu Pippi Salle. (2023) Artificial neural networks for the management of poultry industry: a simulation based on the broiler production chain. Ciência Animal Brasileira 24.
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EB Oliveira, LGB Almeida, DT Rocha, TQ Furian, KA Borges, HLS Moraes, VP Nascimento & CTP Salle. (2022) Artificial Neural Networks to Predict Egg-Production Traits in Commercial Laying Breeder Hens. Brazilian Journal of Poultry Science 24:4.
Crossref
Can Elmar Balas. 2017. Nature-Inspired Computing. Nature-Inspired Computing 476 499 .
V B DONGRE & R S GANDHI. (2016) Applications of artificial neural networks for enhanced livestock productivity: A review. The Indian Journal of Animal Sciences 86:11.
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A?RICA C. NAZARENO, IRAN J. O. DA SILVA & DANIELLE P. B. FERNANDES. (2016) Prediction of mean surface temperature of broiler chicks and load microclimate during transport. Engenharia Agr?cola 36:4, pages 593-603.
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Can Elmar Balas. 2016. Using Decision Support Systems for Transportation Planning Efficiency. Using Decision Support Systems for Transportation Planning Efficiency 36 60 .
Nontawat Bang-iam, Yuthapong Udnan & Prinya Masawat. (2013) Design and fabrication of artificial neural network-digital image-based colorimeter for protein assay in natural rubber latex and medical latex gloves. Microchemical Journal 106, pages 270-275.
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Lucas B. Moraes, Fernando S. Osório, Felipe O. Salle, Guilherme F. Souza, Hamilton L.S. Moraes, Luiz C.B. Fallavena, Luciana R. Santos & Carlos T.P. Salle. (2010) Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks. Pesquisa Veterinária Brasileira 30:4, pages 340-344.
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H. Ahmadi & A. Golian. (2010) Growth analysis of chickens fed diets varying in the percentage of metabolizable energy provided by protein, fat, and carbohydrate through artificial neural network. Poultry Science 89:1, pages 173-179.
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H. Ahmadi, M. Mottaghitalab & N. Nariman-Zadeh. (2007) Group Method of Data Handling-Type Neural Network Prediction of Broiler Performance Based on Dietary Metabolizable Energy, Methionine, and Lysine. Journal of Applied Poultry Research 16:4, pages 494-501.
Crossref
Can Elmar BalasLevent KoçLale Balas. (2006) Closure to “Predictions of Missing Wave Data by Recurrent Neuronets” by Can Elmar Balas, Levent Koç, and Lale Balas. Journal of Waterway, Port, Coastal, and Ocean Engineering 132:1, pages 72-74.
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S. Jaiswal, E.R. Benson, J.C. Bernard & G.L. Van Wicklen. (2005) Neural Network Modelling and Sensitivity Analysis of a Mechanical Poultry Catching System. Biosystems Engineering 92:1, pages 59-68.
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