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This paper describes deep learning models based on convolutional neuralnetworks applied to the problem of predicting EM wave propagation over ruralterrain. A surface integral equation formulation, solved with the method ofmoments and accelerated using the Fast Far Field approximation, is used togenerate synthetic training data which comprises path loss computed overrandomly generated 1D terrain profiles. These are used to train two networks,one based on fractal profiles and one based on profiles generated using aGaussian process. The models show excellent agreement when applied to testprofiles generated using the same statistical process used to create thetraining data and very good accuracy when applied to real life problems.

Site-specific Deep Learning Path Loss Models based on the Method of Moments