Use of polynomial neural network for a mineral prospectivity analysis in a GIS environment
Iyer, V., Fung, C.C., Brown, W. and Gedeon, T. (2004) Use of polynomial neural network for a mineral prospectivity analysis in a GIS environment. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21-24 Nov. 2004, Chiang Mai, Thailand.
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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.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||(c) 2004 IEEE.|
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