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Neural networks prediction of ionic mobilities in SF6-N2 mixture
Joint Authors
Lemzadmi, Ahcene.
Guerroui, Assia.
Burdjiba, Tarik
Musawi, A. k.
Source
Issue
Vol. 14, Issue 1 (31 Mar. 2018), pp.86-94, 9 p.
Publisher
Publication Date
2018-03-31
Country of Publication
Algeria
No. of Pages
9
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Abstract EN
The present work outlines the application of neural networks in the modelling and the Prediction of ionic mobility (μ) in SF6-N2 gas mixture using experimental data.
At higher pressures, the mobility ˇ measured with conventional models is inversely proportional to the gas density (N-1).
Experimental data of ionic mobilities for N2+SF6 have been obtained previously by the use indirect method, which, consists of measuring the voltage-current characteristics of corona discharges.
The results obtained by prediction are significantly consistent with those measured experimentally.
The average relative errors on predicted ionic mobility are found to be less than *10% for training as well as for testing.
Since the average errors are less than 10%, the proposed ANNs technique is highly recommended for the prediction of ionic mobilities of corona discharges in N2+SF6 gas mixtures.
American Psychological Association (APA)
Lemzadmi, Ahcene.& Guerroui, Assia.& Burdjiba, Tarik& Musawi, A. k.. 2018. Neural networks prediction of ionic mobilities in SF6-N2 mixture. Journal of Electrical Systems،Vol. 14, no. 1, pp.86-94.
https://search.emarefa.net/detail/BIM-835976
Modern Language Association (MLA)
Lemzadmi, Ahcene.…[et al.]. Neural networks prediction of ionic mobilities in SF6-N2 mixture. Journal of Electrical Systems Vol. 14, no. 1 (2018), pp.86-94.
https://search.emarefa.net/detail/BIM-835976
American Medical Association (AMA)
Lemzadmi, Ahcene.& Guerroui, Assia.& Burdjiba, Tarik& Musawi, A. k.. Neural networks prediction of ionic mobilities in SF6-N2 mixture. Journal of Electrical Systems. 2018. Vol. 14, no. 1, pp.86-94.
https://search.emarefa.net/detail/BIM-835976
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 94
Record ID
BIM-835976