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Dynamic Equivalents by RHONN

Authors: Victor H. Benitez; Juan M. Ramirez;
Abstract
Abstract This article is aimed to the application of artificial neural networks (ANN) for constructing dynamic equivalents. Neural networks are used to estimate voltages at some special nodes. The use of dynamic ANN allows to quickly reduce the size of the electrical grid due to the rapidity of the training process; this facilitates to study different operating conditions. To quantify the accuracy of results, a root mean square measure is applied to compare signals from the full and the reduced model. The displayed figures and tables prove the applicability and robustness of the proposition.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).7 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
7
Average
Average
Average
Fields of Science (3) View all
Related to Research communities
Energy Research