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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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    Link to Published Version: http://dx.doi.org/10.1109/TENCON.2004.1414619
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    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.

    Publication Type: Conference Paper
    Murdoch Affiliation: School of Information Technology
    Publisher: IEEE
    Copyright: (c) 2004 IEEE.
    Notes: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    URI: http://researchrepository.murdoch.edu.au/id/eprint/621
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