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Data/hora: 13/06/2024 08:35:45

ARTIFICIAL NEURAL NETWORKS FOR PREDICTING ANIMAL THERMAL COMFORT
Provedor de dados: 70
Autores: Borges,Pedro H. M.; Mendoza,Zaíra M. S. H. de; Morais,Pedro H. M.; Santos,Ronei L. dos.
ABSTRACT The objective of this study was to develop artificial neural networks (ANNs) for predicting animal thermal comfort based on temperature and relative humidity of the air for each day of the year. The data on temperature and relative humidity for a 25-year historical series collected at the Padre Ricardo Remetter Conventional Meteorological Station, located in the city of Santo Antônio de Leverger - Mato Grosso (Brazil), were retrieved from the website of the National Institute of Meteorology. According to the day of the year, the temperature and humidity index was determined as a function of the climatic variables. Therefore, the day of the year was the input variable of the neural networks, and the temperature and humidity index (THI) was the...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Time series; Artificial intelligence; Comfort index.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000600844