DocumentCode
1947418
Title
Forecasting Equipment Readiness Based on SVM
Author
XiangBo, Zhang ; Guojian, Mei ; Zongchang, Xu
Author_Institution
Dept. of Tech. Support, Armored Force Eng. Inst., Beijing
Volume
1
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
477
Lastpage
480
Abstract
In the paper, SVM (support vector machines) with SRM is aided to forecast readiness and sustainable capability, which can be improved by machine learning. The status parameters of armored vehicle engine are used as a case to analyses, establishes a model to forecast, which can be optimized in model indexes. Finally, the conclusion comes to the validity of method.
Keywords
learning (artificial intelligence); support vector machines; traffic engineering computing; SVM; armored vehicle engine; forecasting equipment; machine learning; support vector machines; sustainable capability; Arithmetic; Artificial intelligence; Automotive engineering; Competitive intelligence; Engines; Machine learning; Predictive models; Space technology; Support vector machines; Vehicles; Equipment Readiness; Forecast Model; Model Validity; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.1298
Filename
4721790
Link To Document