A new fault diagnosis model of electric power grid based on rough radical basis function neural networks

On the basis of giving a new type of attribute reduction method, a coupling recognition model is established which combines rough set and neural network closely and rebuilt in this paper. The simulation results illustrate that the model reduces subject factors in signal recognition and improves netw...

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Bibliographic Details
Published inDianli Xitong Baohu yu Kongzhi Vol. 37; no. 18; pp. 20 - 24
Main Authors Li, Xiao-Quan, Zhuang, De-Hui, Zhang, Qiang
Format Journal Article
LanguageChinese
Published 01.09.2009
Subjects
Basis functions
Classification
Computer simulation
Control systems
Electric power generation
Electric power grids
Fault diagnosis
Joining
Mathematical models
Neural networks
Permissible error
Radicals
Recognition
Reduction
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ISSN1674-3415

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Summary:On the basis of giving a new type of attribute reduction method, a coupling recognition model is established which combines rough set and neural network closely and rebuilt in this paper. The simulation results illustrate that the model reduces subject factors in signal recognition and improves network's structure, and its recognizing effects are obvious and its classifying ability is strong, as well as the model is very error permissible and explicable. It has very wide foreground.
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ISSN:1674-3415