Application of neural networks to identify features of dynamical grounding systems

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:27:13Z
dc.date.accessioned2022-10-05T13:21:53Z
dc.date.available2014-05-20T13:27:13Z
dc.date.available2022-10-05T13:21:53Z
dc.date.created2014-05-20T13:27:13Z
dc.date.issued2001-01-01
dc.identifierIjcnn'01: International Joint Conference on Neural Networks, Vols 1-4, Proceedings. New York: IEEE, p. 2093-2097, 2001.
dc.identifier1098-7576
dc.identifierhttp://hdl.handle.net/11449/8898
dc.identifier10.1109/IJCNN.2001.938489
dc.identifierWOS:000172784800372
dc.identifier8212775960494686
dc.identifier4517057121462258
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3885390
dc.description.abstractThe accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relationIjcnn'01: International Joint Conference on Neural Networks, Vols 1-4, Proceedings
dc.rightsAcesso aberto
dc.sourceWeb of Science
dc.titleApplication of neural networks to identify features of dynamical grounding systems
dc.typeTrabalho apresentado em evento


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