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Prediction of the Electric Energy System State with the Help of Artificial Neural Networks
- 1.0047395 - ÚI 2007 RIV US eng C - Conference Paper (international conference)
Vítková, G. - Jelínek, J. - Húsek, Dušan - Snášel, Václav
Prediction of the Electric Energy System State with the Help of Artificial Neural Networks.
[Predikce stavů elektrického energetického systému s pomocí neuronových sítí.]
Power, Energy and Applications. Science and Technology for Development in 21st Century. Anheim: ACTA press, 2006 - (Anderson, G.), s. 54-58. ISBN 0-88986-614-7.
[IASTED International Conference on Power, Energy and Applications. Gaborone (BW), 11.09.2006-13.09.2006]
R&D Projects: GA AV ČR 1ET100300414
Institutional research plan: CEZ:AV0Z10300504
Keywords : electricity distribution system * simulation * artificial intelligence * neural networks * backpropagation network * Kohonen network * ART2
Subject RIV: BB - Applied Statistics, Operational Research
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.
Vhodnost aplikace neuronových sítí pro predikci havarijních stavů ve spotřebitelských elektrických sítích je prokázána na základě teoretické analýzy a následné experimentální verifikace. Ukazuje se, že neuronové sítě jsou velmi slibným nástrojem pro tento cíl. Byly testovány 3 síťové architektury: Backpropagation network, Kohonen network a ART2.
Permanent Link: http://hdl.handle.net/11104/0138316
Number of the records: 1