FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
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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Engenharia Agrícola |
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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 |
_version_ |
1752126274068807680 |