Use of polynomial neural network for a mineral prospectivity analysis in a GIS environment | Zendy

V. Iyer | Zendy; C.C. Fung | Zendy; W. Brown | Zendy; T. Gedeon | Zendy

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Use of polynomial neural network for a mineral prospectivity analysis in a GIS environment

Author(s) -

V. Iyer,

C.C. Fung,

W. Brown,

T. Gedeon

Publication year - 2005

Publication title -

2004 ieee region 10 conference tencon 2004.

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1109/tencon.2004.1414619

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , power, energy and industry applications , robotics and control systems

In the mining industry, identifying new geographic locations that are favorable 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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