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Prediction of the Electric Energy System State with the Help of Artificial Neural Networks
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SYSNO ASEP 0047395 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Prediction of the Electric Energy System State with the Help of Artificial Neural Networks Title Predikce stavů elektrického energetického systému s pomocí neuronových sítí Author(s) Vítková, G. (CZ)
Jelínek, J. (CZ)
Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Snášel, Václav (UIVT-O)Source Title Power, Energy and Applications. Science and Technology for Development in 21st Century. - Anheim : ACTA press, 2006 / Anderson G.O. - ISBN 0-88986-614-7 Pages s. 54-58 Number of pages 5 s. Action IASTED International Conference on Power, Energy and Applications Event date 11.09.2006-13.09.2006 VEvent location Gaborone Country BW - Botswana Event type WRD Language eng - English Country US - United States Keywords electricity distribution system ; simulation ; artificial intelligence ; neural networks ; backpropagation network ; Kohonen network ; ART2 Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1ET100300414 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000243783000010 EID SCOPUS 38049160035 Annotation Worthiness of neural networks application for prediction of emergency states in utility networks is proved on the basis of theoretical analysis and its experimental verification. Neural networks appeared to be a very promising means for this objective. Three neural network architectures were tested - Backpropagation network, Kohonen network and ART2. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2007
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