Residual current fault type recognition based on S3VM and KNN cooperative training
Authors:
- 27 July 2022
- journal article
- research article
- Published by Springer Nature in Journal of Power Electronics
- Vol. 22 (11) , 1966-1977
Abstract
No abstract availableKeywords
Funding Information
- Natural Science Foundation of Shandong Province (ZR2020MF124)
- Zibo City Integration Development Project (2019ZBXC011, 2019ZBXC498)
This publication has 18 references indexed in Scilit:
- An efficient semi-supervised SVM for anomaly detection2017
- Fast and simple gradient-based optimization for semi-supervised support vector machinesNeurocomputing, 2014
- Variational Mode DecompositionIEEE Transactions on Signal Processing, 2013
- Fault Diagnosis Based on Novel Hybrid Intelligent ModelChinese Journal of Mechanical Engineering, 2008
- A comparison of PCA, KPCA and ICA for dimensionality reduction in support vector machineNeurocomputing, 2003
- Morphology and Tensile Properties of Polycarbonate-Polyethylene Alloy in Phase Inversion RegionJournal of Elastomers & Plastics, 2003
- An overview of statistical learning theoryIEEE Transactions on Neural Networks, 1999
- Support vector machines for spam categorizationIEEE Transactions on Neural Networks, 1999
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysisProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998
- Comparing support vector machines with Gaussian kernels to radial basis function classifiersIEEE Transactions on Signal Processing, 1997