This paper presents a rule-based expert system for automatic identification and classification of PQ disturbances by combining the improved S-transform and SVM. The combined tools are used to integrate the computation process and extracted features to formulate rules for classification of the PQ disturbances.Rule formulataion is developed by comparing standard deviation value of a disturbance signal that is obtained from the S-transform analysis. SVM technique is used for data classification and regression for training and testing the class level and control feature parameters, respectively.Thus, based on the distinctive features through SVM, the S-Transform formulated appropriate rules and features contour that can easily be classify the PQ disturbances. © 2011 Praise Worthy Prize S.r.l. - All rights reserved.
|Number of pages||2702|
|Journal||International Review on Modelling and Simulations|
|Publication status||Published - 01 Jan 2011|
Hannan, M. A., Wei, T. C., & Wenda, A. (2011). Rule-based expert system for PQ disburbances classification using S-transform and support vector machines. International Review on Modelling and Simulations, 3004-3011.