NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS

Detalhes bibliográficos
Autor(a) principal: Lins,Ana C. de S. S.
Data de Publicação: 2021
Outros Autores: Lourençoni,Dian, Yanagi Júnior,Tadayuki, Miranda,Isadora B., Santos,Italo E. dos A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034
Resumo: ABSTRACT Considering the challenges faced by poultry farming, this study aimed to develop a neuro-fuzzy model to predict eyeball and crest temperatures of egg-laying hens based on environmental conditions (dry bulb temperature and relative humidity). To develop the models and simulations, Matlab’s Fuzzy Toolbox® (Anfisedit) was used. Different configurations were used for each of the several neuro-fuzzy models developed. Eyeball temperature (ET) and chicken crest temperature (CCT) were simulated from the developed neuro-fuzzy models, and the obtained results were validated with the variables collected experimentally with the aid of recorder sensors and an infrared thermographic camera. The proposed neuro-fuzzy models allow the accurate estimation of ET and CCT of two lineages of egg-laying hens raised in conventional aviaries, thus helping in decision-making for better animal welfare.
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spelling NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENSNeuro-fuzzyThermographyPoultry farmingSimulationArtificial intelligenceABSTRACT Considering the challenges faced by poultry farming, this study aimed to develop a neuro-fuzzy model to predict eyeball and crest temperatures of egg-laying hens based on environmental conditions (dry bulb temperature and relative humidity). To develop the models and simulations, Matlab’s Fuzzy Toolbox® (Anfisedit) was used. Different configurations were used for each of the several neuro-fuzzy models developed. Eyeball temperature (ET) and chicken crest temperature (CCT) were simulated from the developed neuro-fuzzy models, and the obtained results were validated with the variables collected experimentally with the aid of recorder sensors and an infrared thermographic camera. The proposed neuro-fuzzy models allow the accurate estimation of ET and CCT of two lineages of egg-laying hens raised in conventional aviaries, thus helping in decision-making for better animal welfare.Associação Brasileira de Engenharia Agrícola2021-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034Engenharia Agrícola v.41 n.1 2021reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v41n1p34-38/2021info:eu-repo/semantics/openAccessLins,Ana C. de S. S.Lourençoni,DianYanagi Júnior,TadayukiMiranda,Isadora B.Santos,Italo E. dos A.eng2021-02-25T00:00:00Zoai:scielo:S0100-69162021000100034Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2021-02-25T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
title NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
spellingShingle NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
Lins,Ana C. de S. S.
Neuro-fuzzy
Thermography
Poultry farming
Simulation
Artificial intelligence
title_short NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
title_full NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
title_fullStr NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
title_full_unstemmed NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
title_sort NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
author Lins,Ana C. de S. S.
author_facet Lins,Ana C. de S. S.
Lourençoni,Dian
Yanagi Júnior,Tadayuki
Miranda,Isadora B.
Santos,Italo E. dos A.
author_role author
author2 Lourençoni,Dian
Yanagi Júnior,Tadayuki
Miranda,Isadora B.
Santos,Italo E. dos A.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Lins,Ana C. de S. S.
Lourençoni,Dian
Yanagi Júnior,Tadayuki
Miranda,Isadora B.
Santos,Italo E. dos A.
dc.subject.por.fl_str_mv Neuro-fuzzy
Thermography
Poultry farming
Simulation
Artificial intelligence
topic Neuro-fuzzy
Thermography
Poultry farming
Simulation
Artificial intelligence
description ABSTRACT Considering the challenges faced by poultry farming, this study aimed to develop a neuro-fuzzy model to predict eyeball and crest temperatures of egg-laying hens based on environmental conditions (dry bulb temperature and relative humidity). To develop the models and simulations, Matlab’s Fuzzy Toolbox® (Anfisedit) was used. Different configurations were used for each of the several neuro-fuzzy models developed. Eyeball temperature (ET) and chicken crest temperature (CCT) were simulated from the developed neuro-fuzzy models, and the obtained results were validated with the variables collected experimentally with the aid of recorder sensors and an infrared thermographic camera. The proposed neuro-fuzzy models allow the accurate estimation of ET and CCT of two lineages of egg-laying hens raised in conventional aviaries, thus helping in decision-making for better animal welfare.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-01
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=S0100-69162021000100034
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v41n1p34-38/2021
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 Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.41 n.1 2021
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
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