Prediction of core losses on a three-phase transformer using neural networks
This work is a study of intelligent tools for forecasting losses in the transformer core, comparing with the traditionally accepted model. The uses of Artificial Neural Networks (ANN) search a best estimator of losses in the transformer core. Two models of ANN were proposed: Multi-Layer Percepton (M...
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Published in | 2011 IEEE International Symposium of Circuits and Systems (ISCAS) pp. 1105 - 1108 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2011
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Subjects | |
Online Access | Get full text |
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Summary: | This work is a study of intelligent tools for forecasting losses in the transformer core, comparing with the traditionally accepted model. The uses of Artificial Neural Networks (ANN) search a best estimator of losses in the transformer core. Two models of ANN were proposed: Multi-Layer Percepton (MLP) and Neo-Fuzzy Neuron (NFN). After an analysis of the model they were evaluated and it was concluded that the MLP model for this application had the best performance. |
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ISBN: | 1424494737 9781424494736 |
ISSN: | 0271-4302 2158-1525 |
DOI: | 10.1109/ISCAS.2011.5937763 |