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Genetic fuzzy system for prediction of respiratory rate of chicks subject to thermal challenges AGRIAMBI
Ferraz,Patrícia F. P.; Yanagi Junior,Tadayuki; Hernandez-Julio,Yamid F.; Ferraz,Gabriel A. e S.; Silva,Maria A. J. G.; Damasceno,Flavio A..
ABSTRACT The aim of this study was to estimate and compare the respiratory rate (breath min-1) of broiler chicks subjected to different heat intensities and exposure durations for the first week of life using a Fuzzy Inference System and a Genetic Fuzzy Rule Based System. The experiment was conducted in four environmentally controlled wind tunnels and using 210 chicks. The Fuzzy Inference System was structured based on two input variables: duration of thermal exposure (in days) and dry bulb temperature (°C), and the output variable was respiratory rate. The Genetic Fuzzy Rule Based System set the parameters of input and output variables of the Fuzzy Inference System model in order to increase the prediction accuracy of the respiratory rate values. The two...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Broiler; Computational intelligence; Physiological responses.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000600412
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