de Souza, A. N.da Silva, I. N.Bordon, M. E.2014-05-202014-05-202000-01-01Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi. Los Alamitos: IEEE Computer Soc, p. 185-190, 2000.1098-7576This gaper demonstrates that artificial neural networks can be used effectively for estimation of parameters related to study of atmospheric conditions to high voltage substations 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.185-190engTrabalho apresentado em evento10.1109/IJCNN.2000.859394WOS:000089240600031Acesso aberto821277596049468655898388442982320000-0001-8510-8245