Adaptive propagation modelling using a hybrid neural network technique

A hybrid modelling approach for the prediction of terrestrial wave propagation is introduced. It is shown that the use of neural networks leads to highly adaptive models by the simultaneous representation of nonlinear dependencies of various environmental parameters. This flexible and computationally effective approach can be used for calibration and as an extension of conventional prediction models