Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/25629
Type: Artigo de periódico
Title: A decision-tree-based model for evaluating the thermal comfort of horses
Author: 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
Abstract: 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 dataset were considered relevant for the classification problem and the decision-tree model yielded an accuracy rate of 74 %. The feature selection methods used to reduce computational cost and simplify predictive learning decreased model accuracy to 70 %; however, the model became simpler with easily interpretable rules. For both these selection methods and for the classification using all attributes, armpit and breast T S had a higher power rating for predicting thermal comfort. Data mining techniques show promise in the discovery of new variables associated with the thermal comfort of horses.
Subject: feature selection methods
data mining
surface temperature
infrared thermography
thermoregulation
Editor: São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"
Rights: aberto
Identifier DOI: 10.1590/S0103-90162013000600001
Address: http://dx.doi.org/10.1590/S0103-90162013000600001
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162013000600001
Date Issue: 1-Dec-2013
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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