Data/hora: 11/06/2024 15:07:52

Biblioteca(s): | Embrapa Unidades Centrais.
Data corrente: | 18/09/2014
Data da última atualização: | 02/06/2017
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.
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.
Título: | Predicting chick body mass by artificial intelligence-based models.
Ano de publicação: | 2014
Fonte/Imprenta: | Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 7, p. 559-568, jul. 2014.
Idioma: | Inglês
Notas: | Título em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial.
Conteúdo: | The objective of this work was to develop, validate, and compare 190 artificial intelligence&#8209;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&#8209;controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21&#8209;day&#8209;old hicks) ? with the variables dry&#8209;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&#8209;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&#8209;making, and they can be embedded in the heating control system.
Palavras-Chave: | Artificial neural networks; Modeling; Neuro-fuzzy network; Thermal comfort.
Thesaurus Nal: | Animal welfare.
Categoria do assunto: | --
URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/item/108680/1/Predicting-chick-body.pdf
Registro original: | Embrapa Unidades Centrais (AI-SEDE)
Exemplares: | AI-SEDE - (56728-1) - UPE - AP - PP - 630.72081 - P474 -  - DIS