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Data Mining Applied to Horse Thermal Comfort

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2012 IX International Livestock Environment Symposium (ILES IX)  ILES12-1253.(doi:10.13031/2013.41556)
Authors:   Ana Paula De Assis Maia, Brenda B. L Medeiros, Rimena A Vercellino, Juliana Sarubbi, Stanley R. M Oliveira, Paulo R Griska, Daniella Jorge Moura
Keywords:   decision tree, thermography, surface temperature, physiological parameters, balancing techniques

Thermal comfort plays a critical role in body temperature regulation. Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis and it can results in a fluctuation of skin temperature. Although thermal comfort of horse has been studied, its relation with surface temperature is rarely seen in the literature. Therefore, the aim of this study was to verify the potential of data mining techniques in knowledge discovery by associating surface temperature with thermal comfort of horses. The decision tree model presented 74.0% of accuracy and all attributes of dataset were considered relevant for the classification problem. The results revealed the potential of data mining techniques to equine thermal comfort classification problems

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