PREDICTION OF THERMAL COMFORT OF BROILER USING DATA MINING - NASCIMENTO, G. R.; NAAS, I. A.; PEREIRA, D. F.; DUTRA JUNIOR, W. M.; MAIA, A. P. A. (Revista Brasileira de Engenharia de Biossistemas, 2011)
The objective of the research was to use data mining techniques to prove the hypothesis from the analysis of decision trees and interesting measures of the generated rules. The experiment was conducted in two poultry houses where they were taken thermographic pictures weekly. Thermal profiles in the photos were collected and plumage surface temperatures in the skin and correlated with temperature and humidity index (THI). By means of decision trees generated in the classification analysis of thermal comfort of the birds that had the highest total accuracy (68%) was the one that used the discretized by the average surface temperatures (low and high), the surface temperature of plumage (STPL) was the root node. The analysis of data mining combined with technology infrared surface showed great potential for the characterization of the environment and predict thermal comfort in broilers chickens.