Nonlinear time series analysis
Nonlinear time series analysis
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Wavelet Transform Based Fuzzy Inference System for Power Quality Classification
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
Self organizing map (SOM) approach for classification of power quality events
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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Using Phase Space Reconstruction (PSR) and Support Vector Machines (SVMs), a novel approach for power disturbance classification is presented. The types of concerned disturbances include voltage sags, voltage swells, voltage interruptions, impulsive transients, harmonics and flickers. PSR is applied for disturbance feature extraction. Based on PSR, power disturbance trajectories are constructed and then converted into binary images through encoding. Four distinctive features are proposed as the inputs of SVM classifier. Simulation results show that the classification method is effective and it requires less training samples.