Wavelet signal energy with RBFNN and GRNN for fault classification in transmission line with series compensator
作者： S. A. Shaaban , M. A. Abdel-Moamen
DOI: 10.1109/IPACT.2017.8244876
关键词:
摘要: Protection of transmission lines including series compensators has been a very important topic. In this paper, wavelet signal energy for fault recognition using advantage combining two types neural networks. Radial Basis Function Neural Network (RBFNN) and General Regression (GRNN) are proposed current voltage signals the compensated line. The algorithm is simple accurate to find out classify types. Several cases studied simulation results presented show effectiveness such algorithm. simulations done in MATLAB® environment.
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