Title :
Neighborhood Based SVM Multi-classification Method for Condition Assessment of Insulator
Author :
Du, Nian ; Zhu, Yongli
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
Support vector machines (SVMs) are a class of popular classification algorithms for high generalization ability. However they mainly solve with two-classification problem, while, in practice, there are lots of multi-classification problem still. Based on advantages and shortcomings of existing multi-classification, a kind of neighborhood based SVM multi-classification method is proposed in this paper. To classify Samples in K classes just need to construct K-1 SVM classifiers with this method. And classifiers at prediction stage are chosen according to neighborhood of test samples. By using neighborhood based SVM and pair wise SVM to train these five stages and forecast respectively, the usefulness of this multi-classification method and more efficient is proved. In addition, an insulator condition valuation model based on neighborhood is obtained.
Keywords :
condition monitoring; insulators; pattern classification; power engineering computing; support vector machines; K-1 SVM classifiers; condition assessment; insulator condition valuation model; neighborhood based SVM multiclassification method; Accuracy; Classification algorithms; Flashover; Insulators; Leakage current; Support vector machines; Training; condition assessment; insulator; multi-classification; neighborhood relation; rough set; support vector machine;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1085-8
DOI :
10.1109/ISCID.2011.180
