Depth estimation of subsurface cavities using Hopfield Neural Networks

The method of Artificial Neural Network is used as a suitable tool for intelligent interpretation of gravity data in this paper. We have designed a Hopfield Neural Network to estimate the gravity source depth. The designed network was tested by both synthetic and real data. As a real data, this Artificial Neural Network was used to estimate the depth of a Qanat located in north entrance of institute of geophysics and the result was very near to the real value of depth.