Using Artificial Neural Networks to Identify Structural Features of the Grounding Processes

A.N. de Souza, F.C. Lyra Amaral, and M.G. Zago (Brazil)


Grounding, Artificial Neural Networks, Lighting, High Voltage.


This paper describes a novel approach to map characteristics of grounding systems using artificial neural networks. The network acts as an 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 concerning lightning.

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