Applications of artificial neural networks to the generation of wave equations from hydraulic data

In this study, existing computational hydraulic engines are used to generate numerical solutions that are treated as 'noiseless' field data. Artificial neural networks (ANNs) are then used to transform this data into what are, in effect, numerical schemes, and these are used in their turn to generate the partial differential equations that govern the observed phenomena. Since it is thereby shown that the trained ANNs can reinstate the governing …