USE OF PERCEPTRON NEURAL NETWORKS AS A TOOL FOR MINERAL POTENTIAL MAPPING IN EGYPT | ||
| Journal of Egyptian Geophysical Society | ||
| Volume 11, Issue 1, 2013, Pages 75-80 PDF (840.25 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jegs.2013.384997 | ||
| Authors | ||
| K.M. Fouad; S.M.M. Hanafy | ||
| Nuclear Materials Authority, P.O. Box 530 El Maadi- Cairo, Egypt. | ||
| Abstract | ||
| A perceptron artificial neural network (PNN) model is proposed to discriminate zones of high mineral potential in the Eastern Desert of Egypt using remote sensing and airborne spectral gamma-ray data stored in a GIS database. A neural network model with one hidden unit was selected by means of a perceptron neuron, which uses the hard-limit transfer function. The trained network delineated a gold potential map efficiently, detected a previously known area as well as a suggested potentially mineralized one. These initial results suggest that PNN can be an effective tool for mineral exploration using spatial data modeling. | ||
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