Earth-return path impedances of underground cables. II. Evaluations using neural networks

For pt.II see ibid., vol.145, no.6, p.621-6 (1998). The aim of the paper is to train an array of neural networks to provide a procedure with high accuracy and low computing time requirement for evaluating the earth-return path impedances of underground cables. The training set required is formed by using a direct numerical integration method to evaluate the infinite integrals in the earth-return path formulations. The training is extensive but, once completed, it is valid for any cable configuration as it arises. The training leads to a universal set of weighting coefficients for an array of networks each of which has three input nodes, one output node and two hidden layers. Set up with these coefficients, the computing time requirements in calculating sets of series-path parameters for underground cables is reduced by a factor of about 1000 from that using a direct numerical evaluation of infinite integrals