Title :
Decision-Improved Support Vector Machine and its Application
Author :
Liu, G.J. ; Liu, X.M. ; Zhang, Ye ; Qiu, Jian
Author_Institution :
Nat. Univ. of Defense Technol., Changsha
Abstract :
The practical applications of 1-SVM in pattern classification are limited due to the deficiency of its low classification precision. Aimed at solving this problem, first, a 1-DISVM is proposed, in which a coefficient is introduced to adjust decision curve region. Compared to 1-SVM, 1-DISVM inherits the ability to find outliers but gains improved classification accuracy by the coefficient adjusting. Based on 1-DISVM, an unsupervised learning multi-class classification model is also built. By means of small quantity of fault samples, the model improves classification performance by getting rid of the influence from wrong samples. Then the experiment is implemented by applying the considered approaches in gear-box fault diagnosis. Experimental results show that, the presented method achieved precise classification for two-class (normal and fault) data identification.
Keywords :
decision making; pattern classification; support vector machines; unsupervised learning; classification accuracy; data identification; decision curve region; decision-improved support vector machine; gear-box fault diagnosis; multiclass classification; pattern classification; unsupervised learning; Artificial intelligence; Artificial neural networks; Fault diagnosis; Intelligent networks; Kernel; Pattern classification; Space technology; Support vector machine classification; Support vector machines; Unsupervised learning;
Conference_Titel :
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1685-1
Electronic_ISBN :
978-1-4244-1686-8
DOI :
10.1109/ICNSC.2008.4525283
