Use of Polynomial Neural Network for a mineral prospectivity analysis in a GIS environment
Date
2004
Authors
Iyer, Vanaja
Fung, Chun Che
Brown, Warwick
Gedeon, Tamas (Tom)
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Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
In the mining industry, identifying new geographic locations that are favourable for mineral exploration is very important. However definitive prediction of such locations is not an easy task. In the recent years artificial neural networks have received much attention in this area. This paper uses a class of neural networks known as the Polynomial Neural Network (PNN) to construct a model to correctly classify given location into deposit and barren areas. This model uses the Geographic Information Systems (GIS) data of the location. The method is tested on the GIS data for the Kalgoorlie region of Western Australia.
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Keywords
Keywords: Geographical regions; Mineral exploration; Neural networks; Polynomials; Geographic locations; Polynomial neural networks; Geographic information systems Geographical Information System; Mineral prospectivity; Polynomial neural network
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Proceedings of the IEEE Region 10 Conference (TenCon 04)
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Conference paper
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Restricted until
2037-12-31
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