Egg hatchability prediction by multiple linear regression and artificial neural networks

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dc.creatorAC Bolzan
dc.creatorRAF Machado
dc.creatorJCZ Piaia
dc.date2008
dc.date.accessioned2026-07-07T03:23:15Z
dc.descriptionAn artificial neural network (ANN) was compared with a multiple linear regression statistical method to predict hatchability in an artificial incubation process. A feedforward neural network architecture was applied. Network trainings were made by the backpropagation algorithm based on data obtained from industrial incubations. The ANN model was chosen as it produced data that fit better the experimental data as compared to the multiple linear regression model, which used coefficients determined by minimum square method. The proposed simulation results of these approaches indicate that this ANN can be used for incubation performance prediction.
dc.formatapplication/pdf
dc.identifier1516-635X
dc.identifierhttps://www.redalyc.org/articulo.oa?id=179713999004
dc.identifier.urihttp://hdl.handle.net/123456789/432327
dc.languageen
dc.publisherFundação APINCO de Ciência e Tecnologia Avícolas
dc.relationhttp://www.redalyc.org/revista.oa?id=1797
dc.rightsRevista Brasileira de Ciência Avícola
dc.sourceRevista Brasileira de Ciência Avícola (Brasil) Num.2 Vol.10
dc.subjectAgrociencias
dc.titleEgg hatchability prediction by multiple linear regression and artificial neural networks
dc.typeartículo científico

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Revista Brasileira de Ciência Avícola - Fundação APINCO de Ciência e Tecnologia Avícolas