Genetic fuzzy system for prediction of respiratory rate of chicks subject to thermal challenges

Revista Brasileira de Engenharia Agricola e Ambiental

Yanagi Junior, Tadayuki¹  Ferraz, Patrícia F. P.² 

[1] Universidad del Sinú Elías Bechara Zainúm, Montería, Colombia;Universidade Federal de Lavras, Lavras, Brazil

关键词: broiler;    computational intelligence;    physiological responses.;   

DOI  :  10.1590/1807-1929/agriambi.v22n6p412-417

学科分类：农业科学（综合）

来源: Universidade Federal de Campina Grande * Centro de Ciencias e Tecnologia

【 摘 要 】

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 systems (Fuzzy Inference System and Genetic Fuzzy Rule Based System) proved to be able to predict the respiratory rate of chicks. The Genetic Fuzzy Rule Based System interacted well with the Fuzzy Inference System model previously developed showing an improvement in the respiratory rate prediction accuracy. The Fuzzy Inference System had mean percentage error of 2.77, and for Fuzzy Inference System and Genetic Fuzzy Rule Based System it was 0.87, thus indicating an improvement in the accuracy of prediction of respiratory rate when using the tool of genetic algorithms.

【 授权许可】

CC BY