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