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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Boosting Algorithm to Improve a Voltage Waveform Classifier Based on Artificial Neural Network
verfasst von : Milde M. S. Lira, Ronaldo R. B. de Aquino, Aida A. Ferreira, Manoel A. Carvalho Jr., Otoni Nóbrega Neto, Gabriela S. M. Santos, Carlos Alberto B. O. Lira
Erschienen in: Artificial Neural Networks – ICANN 2007
Verlag: Springer Berlin Heidelberg
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An ANN-based classifier for voltage wave disturbance was developed. Voltage signals captured on the power transmission system of CHESF, Federal Power Utility, were processed in two steps: by wavelet transform and principal component analysis. The classification was carried out using a combination of six MLPs with different architectures: five representing the first to fifth-level details, and one representing the fifth-level approximation. Network combination was formed using the boosting algorithm which weights a model’s contribution by its performance rather than giving equal weight to all models. Experimental results with real data indicate that boosting is clearly an effective way to improve disturbance classification accuracy when compared with the simple average and the individual models.