Publicação: Evaluation and identification of lightning models by artificial neural networks
Carregando...
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Tipo
Trabalho apresentado em evento
Direito de acesso
Acesso aberto
Resumo
This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.
Descrição
Palavras-chave
Atmospheric humidity, Computer simulation, Electric fields, Electric potential, Lightning, Mathematical models, Pressure effects, Thermal effects, Waveform analysis, Critical disruptive voltage, Electrical field intensity, Neural networks
Idioma
Inglês
Como citar
Proceedings of the International Joint Conference on Neural Networks, v. 6, p. 3816-3820.
