Fuzzy Neural Network for Pattern Recognition of Power System Events: Fuzzy Neura

Description: Fuzzy Neural Network for Pattern Recognition of Power System Events by Slavko Vasilic An advanced artificial intelligence based algorithm for detecting and classifying faults on the power system transmission line is introduced. The approach utilizes self-organized, Adaptive Resonance Theory (ART) neural network, combined with fuzzy decision rule for interpretation of neural network outputs. Training of the neural network is based on the combined use of unsupervised and supervised learning methods. During training, a set of input events is transformed into a set of prototypes of typical input events. During application, real events are classified based on the interpretation of their matching to the prototypes through fuzzy decision rule. This study introduces several enhancements to the original version of the ART algorithm: suitable preprocessing of neural network inputs, improvement in the concept of supervised learning, fuzzyfication of neural network outputs, and utilization of on- line learning. Simulation results show improved recognition capabilities compared to a previous version of ART neural network algorithm, Multilayer Perceptron (MLP) neural network algorithm, and impedance based distance relay FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description An advanced artificial intelligence based algorithm for detecting and classifying faults on the power system transmission line is introduced. The approach utilizes self-organized, Adaptive Resonance Theory (ART) neural network, combined with fuzzy decision rule for interpretation of neural network outputs. Training of the neural network is based on the combined use of unsupervised and supervised learning methods. During training, a set of input events is transformed into a set of prototypes of typical input events. During application, real events are classified based on the interpretation of their matching to the prototypes through fuzzy decision rule. This study introduces several enhancements to the original version of the ART algorithm: suitable preprocessing of neural network inputs, improvement in the concept of supervised learning, fuzzyfication of neural network outputs, and utilization of on- line learning. Simulation results show improved recognition capabilities compared to a previous version of ART neural network algorithm, Multilayer Perceptron (MLP) neural network algorithm, and impedance based distance relay Author Biography Slavko Vasilic received his Ph.D in Electrical Engineering from Texas A&M University in 2004, and M.S.E.E. from University of Belgrade in 1999. He specializes in power systems, control systems, signal processing and artificial intelligence. He is a registered professional engineer in California and Maryland, and a member of IEEE. Details ISBN3639216733 Author Slavko Vasilic ISBN-10 3639216733 ISBN-13 9783639216738 Media Book Format Paperback Publication Date 2009-12-21 Short Title FUZZY NEURAL NETWORK FOR PATTE Pages 144 Language English Year 2009 Subtitle Fuzzy Neural Network Pattern Recognition Algorithm for Classification of the Events in Power System Networks UK Release Date 2009-12-21 Imprint VDM Verlag Country of Publication Germany Illustrations black & white illustrations Publisher VDM Verlag Audience General We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:132423314;

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