Registro completo |
Provedor de dados: |
REA
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País: |
Brazil
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Título: |
NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
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Autores: |
Lins,Ana C. de S. S.
Lourençoni,Dian
Yanagi Júnior,Tadayuki
Miranda,Isadora B.
Santos,Italo E. dos A.
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Data: |
2021-02-01
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Ano: |
2021
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Palavras-chave: |
Neuro-fuzzy
Thermography
Poultry farming
Simulation
Artificial intelligence
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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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Tipo: |
Info:eu-repo/semantics/article
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Idioma: |
Inglês
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Identificador: |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034
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Editor: |
Associação Brasileira de Engenharia Agrícola
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Relação: |
10.1590/1809-4430-eng.agric.v41n1p34-38/2021
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Formato: |
text/html
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Fonte: |
Engenharia Agrícola v.41 n.1 2021
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Direitos: |
info:eu-repo/semantics/openAccess
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