Calculation of breakdown voltages in Ar+SF/sub 6/ using an artificial neural network
An artificial neural network is proposed to predict the breakdown voltages in Ar+SF/sub 6/ gas mixtures. The proposed neural network is designed with one hidden layer that includes twenty-five neurons. The output layer of the ANN consists of one neuron, which is essentially the predicted breakdown v...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | An artificial neural network is proposed to predict the breakdown voltages in Ar+SF/sub 6/ gas mixtures. The proposed neural network is designed with one hidden layer that includes twenty-five neurons. The output layer of the ANN consists of one neuron, which is essentially the predicted breakdown voltage. In order to train the ANN, the experimental data available for Ar+SF/sub 6/ have been used. The results of this ANN are compared with the experimental data as well as calculated data using the streamer criterion. With the proposed ANN, the average relative errors on breakdown voltages are found to be 3.85% for training and 4.32% for testing. Since the average errors are less than 5%, it is recommended to use ANN to predict the breakdown voltages. |
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ISSN: | 0084-9162 2576-2397 |
DOI: | 10.1109/CEIDP.2005.1560620 |