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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6
Artificial Neural Networks Applied in Study of Atmospheric Parameters to High Voltage Substations Concerning Lightning
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
ASCII Text
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André N. de Souza, Ivan N. da Silva, Mario E. Bordon, "Artificial Neural Networks Applied in Study of Atmospheric Parameters to High Voltage Substations Concerning Lightning," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 6, pp. 6185, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.859394,
author = {André N. de Souza and Ivan N. da Silva and Mario E. Bordon},
title = {Artificial Neural Networks Applied in Study of Atmospheric Parameters to High Voltage Substations Concerning Lightning},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {6},
year = {2000},
issn = {1098-7576},
pages = {6185},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.859394},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - Artificial Neural Networks Applied in Study of Atmospheric Parameters to High Voltage Substations Concerning Lightning
SN - 1098-7576
SP
EP
A1 - André N. de Souza,
A1 - Ivan N. da Silva,
A1 - Mario E. Bordon,
PY - 2000
VL - 6
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
André N. de Souza, University of S?o Paulo
Ivan N. da Silva, University of S?o Paulo
Mario E. Bordon, University of S?o Paulo
This paper demonstrates that artificial neural networks can be used effectively for estimation of parameters related to study of atmospheric conditions to high voltage substation design. Specifically, the neural networks are used to compute the variation of electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric factors, such as pressure, temperature, humidity, so on. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the verification of the influence of the atmospheric conditions on design of substations concerning lightning.
Citation:
André N. de Souza, Ivan N. da Silva, Mario E. Bordon, "Artificial Neural Networks Applied in Study of Atmospheric Parameters to High Voltage Substations Concerning Lightning," ijcnn, vol. 6, pp.6185, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6, 2000
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