Cart (Loading....) | Create Account
Close category search window
 

Detection of Power Quality Events Using DOST-Based Support Vector Machines

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Kaewarsa, S. ; Sch. of Electr. Eng., Rajamangala Univ. of Technol. Isan, Sakon Nakhon

This paper presents a method based on discrete orthogonal S-transform (DOST) and support vector machines (SVM) for detection and classification of power quality events. DOS-transform is mainly used to extract features of power quality events and support vector machines are mainly used to construct a multi-class classifier which can classify power quality events according to the extracted features. Results of simulation and analysis demonstrate that the proposed method can achieve higher correct identification rate, better convergence property and less training time compared with the method based on neural network.

Published in:

Computer Science and its Applications, 2008. CSA '08. International Symposium on

Date of Conference:

13-15 Oct. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.