Data/hora: 03/06/2024 01:14:20

Provedor de dados: 	70	
País: 	Brazil	
Título: 	NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS	
Autores: 	Lins,Ana C. de S. S.; Lourençoni,Dian; Yanagi Júnior,Tadayuki; Miranda,Isadora B.; Santos,Italo E. dos A.	
Data: 	2021-02-01	
Ano: 	2021	
Palavras-chave: 	Neuro-fuzzy; Thermography; Poultry farming; Simulation; Artificial intelligence.	
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.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034	
Editor: 	Associação Brasileira de Engenharia Agrícola	
Relação: 	10.1590/1809-4430-eng.agric.v41n1p34-38/2021	
Formato: 	text/html	
Fonte: 	Engenharia Agrícola  v.41 n.1 2021	
Fonte: 	info:eu-repo/semantics/openAccess