Autors: TOPALOV,S., HRISTOV.V.
Title: Investigation of 3D copper grade changeability by Neural Networks in metasomatic ore deposit
Keywords: ore deposit, exploration, 3D (spatial) exploration data, ope

Abstract: The following neural networks (NN) types: Radial Basis Function (RBF), Generalized Regression Neural Networks (GRNN), and two/three layers Multilayer Perceptron (MLP 2, MLP 3) were examined and MLP2 and MLP3 ware determined as a suitable for the copper grade prognostication on one layer of ore deposit. In this paper following the same approach we attempt to determine the potentialities of the same NN types for copper grade prognostication to the deeper levels of the open pit mine. This approach of 3D training and testing of NN efficiency for prognostication is realized with raw exploration data in metasomatic ore deposit.

References

    Issue

    9th WSEAS International Conference on NEURAL NETWORKS (NN’08), pp. 58-62, 2008, Bulgaria,

    Вид: публикация в национален форум