DocumentCode :
723945
Title :
Approach to radiation temperature measuring and its application via support vector machine
Author :
Yan Ren ; Xiaomin Zhou ; Yanjun Lu ; Li Fu ; Rui Fang
Author_Institution :
Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
fYear :
2015
fDate :
23-25 May 2015
Firstpage :
6476
Lastpage :
6479
Abstract :
This paper presents a measuring method based on Support Vector Machine(SVM), which is used to solve the high temperature measuring problem. As we all known, it is difficult to measure directly in complex industrial environment. Thus, the normal support vector machine(NOR-SVM) is improved, and then a new regression algorithm is proposed. Simulation results demonstrate that the improved algorithm has good nonlinear modeling, generalization ability and predictive ability. What´s more, this model needs less Support Vectors(SVs), so it learns more faster.
Keywords :
computerised instrumentation; regression analysis; support vector machines; temperature measurement; NOR-SVM; normal support vector machine; radiation temperature measurement; regression algorithm; Image color analysis; Mathematical model; Prediction algorithms; Predictive models; Support vector machines; Temperature measurement; Training; Learning Speed; Nonlinear Relationship; SVM; Temperature Measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
Type :
conf
DOI :
10.1109/CCDC.2015.7161985
Filename :
7161985
Link To Document :
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