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| Maia,Ana Paula de Assis; Oliveira,Stanley Robson de Medeiros; Moura,Daniella Jorge de; Sarubbi,Juliana; Vercellino,Rimena do Amaral; Medeiros,Brenda Batista Lemos; Griska,Paulo Roberto. |
| Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S). This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Feature selection methods; Data mining; Surface temperature; Infrared thermography; Thermoregulation. |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162013000600001 |
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