Power systems disturbance classification using modular neural networks with multilayers experts

Abstract

This work evaluates the effectiveness of a new hybrid algorithm in the training of modular neural networks with multilayers specialists. The algorithm is applied on the classification of electric disturbances previously characterized and pre-processed, making possible the comparison between its performance with multilayers perceptrons networks. It presents the algorithm’s development and inclusion of delta-bar-delta rule, such as the data acquisition methodology and its preprocessing.