DocumentCode :
532444
Title :
Expenses estimated for the equipment based on the optimal parameters ε -SVR
Author :
Sun Lin-kai ; Jin Jia-shan ; Geng Jun-bao
Author_Institution :
Sch. of Naval Archit. & Power, Naval Univ. of Eng., Wuhan, China
Volume :
6
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Support vector regression machine (SVR) can establish the expenses estimate model according to the principle of the structure minimum risk. It reaches better accuracy in the small sample estimated, but there are not a set of integrity theories for choosing the parameters of SVR. This paper adopts the methods of varied step to search the optimal parameters. It use the combination accuracy to evaluate the estimated effect, research the influence of the parameters combined form to the estimated accuracy. Then we can assurance the optimized combined form of the parameters. The example indicates the optimized combined form of the parameters can improved the expenses estimated accuracy.
Keywords :
equipment evaluation; life cycle costing; regression analysis; risk analysis; support vector machines; expenses estimate model; life cycle cost; optimal parameters ε-SVR; structure minimum risk; support vector regression machine; ε -Support vector regression machine (ε -SVR); expenses estimated; kenal function; optimal parameter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620545
Filename :
5620545
Link To Document :
بازگشت