Title :
Combining Multiple Artificial Neural Networks Using Random Committee to Decide upon Electrical Disturbance Classification
Author :
Lira, Milde M S ; De Aquino, Ronaldo R B ; Ferreira, Aida A. ; Carvalho, Manoel A., Jr. ; Neto, Otoni Nóbrega ; Santos, Gabriela S M
Author_Institution :
Fed. Univ. of Pernambuco, Recife
Abstract :
An ANN-based automatic classifier for power system disturbance waveforms was developed. Actual voltage waveforms were applied in the training process. Signals were processed in two steps: i) decomposition through wavelet transformation up to the 5th decomposition level; ii) the resultant wavelet coefficients are processed via PCA, reducing the input space of the classifier to a much lower dimension. 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. The RPROP algorithm was applied for training the networks. Network combination was formed using random committee which builds an ensemble of randomized base classifiers. Experimental results with real data indicate that the random committee is clearly an effective way to improve disturbance classification accuracy when compared with the simple average and the individual models.
Keywords :
multilayer perceptrons; power engineering computing; power system faults; principal component analysis; wavelet transforms; ANN-based automatic classifier; MLP; PCA; electrical disturbance classification; fifth-level approximation; multiple artificial neural networks; power system disturbance waveforms; random committee; resultant wavelet coefficients; Artificial neural networks; Inspection; Monitoring; Power system analysis computing; Power system modeling; Principal component analysis; Signal analysis; Time frequency analysis; Voltage; Wavelet coefficients;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371414