To improve the classification accuracy of multiple power quality disturbances, we proposed
a hybrid kernel function support vector machine (HSVM) based on the particle swarm …

A hybrid kernel function of support vector machine is proposed to improve the classification
performance of power quality disturbances. The kernel function mathematical model of …

To improve classification accuracy of the multiple power quality disturbances, a method is
proposed based on the wavelet transform and the particle swarm optimization-support …

This paper, by using support vector machine (SVM) identification of power quality
disturbance signals are classified. In order to obtain better classification results, we need to …

In this paper, an improved one-against-one support vector machine algorithm is used to
classify multiple power quality disturbances. To solve the problem of parameter selection, an …

In this paper, 11 different power quality disturbances were automatically detected by using
statistical features with wavelet transform and norm entropy techniques. The best of the …

Aiming at the problems of difficult manual selection of features, cumbersome classification
steps and low accuracy in traditional power quality disturbance classification methods, a …

This paper presents a S-transform effective feature extraction method for power quality (PQ)
disturbance classification problem. Firstly, S-transform technique is used to extract the …

This paper presents a wavelet transform and Support Vector Machine (SVM) based
algorithm for classification of power quality (PQ) disturbances. The features extracted …

this paper used the multi-class classification for support vector machine and combined with
the good amplitude-frequency characteristic of fourier transform, the good time-frequency …