SVM and Classification Ensembles based High-voltage Transmission Line Fault Diagnosis

Abstract

This paper analyzes the inner mechanism of basic methods for high-voltage transmission line (HTL) fault diagnosis, and proposes the new SVM based HTL diagnosis models, which has the characteristic of good generalization. We also put forward the neural network ensembles model and multiple kinds of classifiers ensembles model based on the technology of classifier ensembles. These models can further promote the performance of single classifiers, such as traditional NN, rough set rules classifier, SVM etc. The simulation and experiments results completely show that our new models are more efficient than traditional ones

DOI: 10.1109/CIT.2005.180

7 Figures and Tables

Cite this paper

@article{Shen2005SVMAC, title={SVM and Classification Ensembles based High-voltage Transmission Line Fault Diagnosis}, author={Bin Shen and Min Yao and Yuan Bo}, journal={The Fifth International Conference on Computer and Information Technology (CIT'05)}, year={2005}, pages={11-17} }