DocumentCode
2463850
Title
Mahalanobis Space Learning Machine for Quality Diagnosis
Author
Zeng Jianghui ; Wang Bangjun ; Hao Jianchun ; Fang, Fang
Author_Institution
Quality Eng. Center, China Aero- Polytechnology Establ., Beijing, China
Volume
3
fYear
2010
fDate
16-17 Dec. 2010
Firstpage
106
Lastpage
110
Abstract
In this paper, a pattern classification algorithm based on Mahalanobis space and its solving via second order cone programming were discussed. The method of selecting feature through Mahalanobis Taguchi System and integrating the Mahalanobis Taguchi System and Mahalanobis space learning machine for pattern classification were proposed. At last, an example of gear quality diagnosis was presented on real data, and the effect of this methodology was proved.
Keywords
Taguchi methods; learning (artificial intelligence); pattern classification; support vector machines; Mahalanobis Taguchi System; Mahalanobis space learning machine; feature selection; pattern classification algorithm; quality diagnosis; second order cone programming; support vector machines; Covariance matrix; Gears; Kernel; Machine learning; Support vector machines; Testing; Training; Mahalanobis Space; Pattern classification; learning machine; quality diagnosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-9247-3
Type
conf
DOI
10.1109/GCIS.2010.215
Filename
5709334
Link To Document