Application of Fuzzy Support Vector Machines to Partial Discharge Pattern Recognition

DOI

10.2991/iccasm.2012.383How to use a DOI?

Keywords

Partial Discharge (PD), Pattern Recognition, Fuzzy Support Vector Machines

Abstract

In the field of pattern recognition, Support Vector Machines (SVMs) has great advantage than other traditional methods due to its simple structure, strong ability of generalization and good performance in recognizing. The feature of discharge is extracted using the 2D pattern chart and the Fuzzy Support Vector Machines (FSVMs) based on the affinity among samples is used to recognize the discharge models in this paper. Experimental results show that FSVMs has the better robust and classification performance than the SVMs.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lihua Fu
AU  - Wanzhong Lei
AU  - Xiaomei Zhang
PY  - 2012/08
DA  - 2012/08
TI  - Application of Fuzzy Support Vector Machines to Partial Discharge Pattern Recognition
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 1498
EP  - 1501
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.383
DO  - 10.2991/iccasm.2012.383
ID  - Fu2012/08
ER  -