Journal Paper

Paper Information

Journal: زمین
Year:1391 | Volume:7 | Issue:23
Start Page:113 | End Page:124

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Title

2-D FORWARD MODELING OF NEAR SURFACE GRAVITY ANOMALY BY USING OF FORCED NEURAL NETWORKS METHOD

Pages

 Start Page 113 | End Page 124

Abstract

 In this paper, we use a new method called FORCED NEURAL NETWORKS (FNN) to find the parameters of buried deposit in geophysical section respect to GRAVITY ANOMALY assuming the prismatic model. The aim of the geological MODELING is to find the shape and location of underground structures in 2-D cross section. Here, one neuron network and back propagation algoritm are applied to fined out the density difference. The method is used for noise-free and noise-corruption synthetic data, and then the Dehloran bitumen field map in Iran is chosen as a real data.

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