THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE

Detalhes bibliográficos
Autor(a) principal: Sangoi,Luiz Fernando
Data de Publicação: 2016
Outros Autores: Kessler,Alexandre de Mello, Neuenfeldt Júnior,Alvaro Luiz, Siluk,Julio Cezar Mairesse, Ribeiro,Andréa Machado Leal, Soliman,Marlon
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000100067
Resumo: ABSTRACT In similar conditions of food handling and genetics, there are large differences in the final productivity of farms, resulting from inherent factors of the production system. This fact predisposes the need of studies on optimizing the rearing conditions of the farms, in order to verify the main limitations for the producers. Therefore, the present study aims to generate predictions of the swine productivity in the finishing phase, using variables related to their profiles and the production results achieved. 107 farmers belonging to a swine cooperative were considered in the study, located in 47 counties at the Taquari valley region, Brazil. Predictions were generated through the aid of neural networks, and the findings show that Artificial Neural Networks (ANN) can predict the productivity variables Feed Conversion, Mortality and Average Daily Gain for the proposed case.
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spelling THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTUREswine cultureArtificial Neural NetworkscompetitivenessABSTRACT In similar conditions of food handling and genetics, there are large differences in the final productivity of farms, resulting from inherent factors of the production system. This fact predisposes the need of studies on optimizing the rearing conditions of the farms, in order to verify the main limitations for the producers. Therefore, the present study aims to generate predictions of the swine productivity in the finishing phase, using variables related to their profiles and the production results achieved. 107 farmers belonging to a swine cooperative were considered in the study, located in 47 counties at the Taquari valley region, Brazil. Predictions were generated through the aid of neural networks, and the findings show that Artificial Neural Networks (ANN) can predict the productivity variables Feed Conversion, Mortality and Average Daily Gain for the proposed case.Sociedade Brasileira de Pesquisa Operacional2016-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000100067Pesquisa Operacional v.36 n.1 2016reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2016.036.01.0067info:eu-repo/semantics/openAccessSangoi,Luiz FernandoKessler,Alexandre de MelloNeuenfeldt Júnior,Alvaro LuizSiluk,Julio Cezar MairesseRibeiro,Andréa Machado LealSoliman,Marloneng2016-06-14T00:00:00Zoai:scielo:S0101-74382016000100067Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2016-06-14T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
title THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
spellingShingle THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
Sangoi,Luiz Fernando
swine culture
Artificial Neural Networks
competitiveness
title_short THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
title_full THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
title_fullStr THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
title_full_unstemmed THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
title_sort THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
author Sangoi,Luiz Fernando
author_facet Sangoi,Luiz Fernando
Kessler,Alexandre de Mello
Neuenfeldt Júnior,Alvaro Luiz
Siluk,Julio Cezar Mairesse
Ribeiro,Andréa Machado Leal
Soliman,Marlon
author_role author
author2 Kessler,Alexandre de Mello
Neuenfeldt Júnior,Alvaro Luiz
Siluk,Julio Cezar Mairesse
Ribeiro,Andréa Machado Leal
Soliman,Marlon
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Sangoi,Luiz Fernando
Kessler,Alexandre de Mello
Neuenfeldt Júnior,Alvaro Luiz
Siluk,Julio Cezar Mairesse
Ribeiro,Andréa Machado Leal
Soliman,Marlon
dc.subject.por.fl_str_mv swine culture
Artificial Neural Networks
competitiveness
topic swine culture
Artificial Neural Networks
competitiveness
description ABSTRACT In similar conditions of food handling and genetics, there are large differences in the final productivity of farms, resulting from inherent factors of the production system. This fact predisposes the need of studies on optimizing the rearing conditions of the farms, in order to verify the main limitations for the producers. Therefore, the present study aims to generate predictions of the swine productivity in the finishing phase, using variables related to their profiles and the production results achieved. 107 farmers belonging to a swine cooperative were considered in the study, located in 47 counties at the Taquari valley region, Brazil. Predictions were generated through the aid of neural networks, and the findings show that Artificial Neural Networks (ANN) can predict the productivity variables Feed Conversion, Mortality and Average Daily Gain for the proposed case.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000100067
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000100067
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2016.036.01.0067
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.36 n.1 2016
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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