FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS

Detalhes bibliográficos
Autor(a) principal: Abreu,Lucas H. P.
Data de Publicação: 2019
Outros Autores: Yanagi Junior,Tadayuki, Campos,Alessandro T., Lourençoni,Dian, Bahuti,Marcelo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100018
Resumo: ABSTRACT Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed fuzzy model was used to predict the cloacal temperature of broiler chickens on the day of thermal stress as a function of air dry-bulb temperature (°C), stress duration (days), and the number of days after thermal stress. Cloacal temperature values simulated by the fuzzy model showed standard deviations and percentage errors lower than 0.02 and 0.08%, respectively, when compared to those obtained experimentally.
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spelling FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESSphysiological responsethermal environmentmathematical modelingfuzzy logicABSTRACT Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed fuzzy model was used to predict the cloacal temperature of broiler chickens on the day of thermal stress as a function of air dry-bulb temperature (°C), stress duration (days), and the number of days after thermal stress. Cloacal temperature values simulated by the fuzzy model showed standard deviations and percentage errors lower than 0.02 and 0.08%, respectively, when compared to those obtained experimentally.Associação Brasileira de Engenharia Agrícola2019-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100018Engenharia Agrícola v.39 n.1 2019reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v39n1p18-25/2019info:eu-repo/semantics/openAccessAbreu,Lucas H. P.Yanagi Junior,TadayukiCampos,Alessandro T.Lourençoni,DianBahuti,Marceloeng2019-02-26T00:00:00Zoai:scielo:S0100-69162019000100018Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2019-02-26T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
title FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
spellingShingle FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
Abreu,Lucas H. P.
physiological response
thermal environment
mathematical modeling
fuzzy logic
title_short FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
title_full FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
title_fullStr FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
title_full_unstemmed FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
title_sort FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
author Abreu,Lucas H. P.
author_facet Abreu,Lucas H. P.
Yanagi Junior,Tadayuki
Campos,Alessandro T.
Lourençoni,Dian
Bahuti,Marcelo
author_role author
author2 Yanagi Junior,Tadayuki
Campos,Alessandro T.
Lourençoni,Dian
Bahuti,Marcelo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Abreu,Lucas H. P.
Yanagi Junior,Tadayuki
Campos,Alessandro T.
Lourençoni,Dian
Bahuti,Marcelo
dc.subject.por.fl_str_mv physiological response
thermal environment
mathematical modeling
fuzzy logic
topic physiological response
thermal environment
mathematical modeling
fuzzy logic
description ABSTRACT Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed fuzzy model was used to predict the cloacal temperature of broiler chickens on the day of thermal stress as a function of air dry-bulb temperature (°C), stress duration (days), and the number of days after thermal stress. Cloacal temperature values simulated by the fuzzy model showed standard deviations and percentage errors lower than 0.02 and 0.08%, respectively, when compared to those obtained experimentally.
publishDate 2019
dc.date.none.fl_str_mv 2019-02-01
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=S0100-69162019000100018
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100018
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v39n1p18-25/2019
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.39 n.1 2019
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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