The Application of Epsilon-SVR in Infrared Temperature Demarcating

A epsiv-SVR (epsiv-Support Vector Regression) based modeling method is introduced to process data acquired from infrared temperature demarcating experiment. In the process of the temperature of black body ranging from 30degC to 72degC, 22 groups of samples are acquired, which include 17 groups of tr...

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Bibliographische Detailangaben
Hauptverfasser:	Sun, Jian, Chen, Liang, Fu, Yaqiong, Wu, Juan, Chen, Le
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Curve fitting Information processing Infrared detectors Infrared imaging infrared temperature demarcating Least squares methods Mathematical model Power system reliability Support vector machine classification Support vector machines Temperature measurement ε -SVR
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Beschreibung
Zusammenfassung:	A epsiv-SVR (epsiv-Support Vector Regression) based modeling method is introduced to process data acquired from infrared temperature demarcating experiment. In the process of the temperature of black body ranging from 30degC to 72degC, 22 groups of samples are acquired, which include 17 groups of training samples and 5 groups of forecasting samples. The fitting curves are got through training samples and forecasting samples under MATLAB. Compared with traditional method of least square, the precision of this method is far higher. In conclusion, the method of epsiv-SVR can become a method of data processing to infrared temperature demarcating.
DOI:	10.1109/APCIP.2009.14