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
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;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161985