Title :
Mineral potential mapping using feed-forward neural networks
Author_Institution :
Sch. of Inf. Technol., Deakin Univ., Burwood, Vic., Australia
Abstract :
Mineral potential mapping is the process of producing a map that depicts the favorability of mineralization occurring over a specified region. The map should reflect the location of known mineral occurrences and also predict the distribution of areas of high mineral potential where little or no mining activity currently exists. Although the development of geographic information system technology and digital data manipulation techniques has enabled mineral exploration geologists to make more efficient use of resource information, many of the methods used are still inherently based on traditional techniques of map stacking in which layers of data are combined under the guidance of a mineral deposition model. This paper describes a data-driven mineral potential mapping technique based on feed-forward neural networks. Results are provided from applying the technique to gold exploration in a region of South West Victoria, Australia, using a range of geological, geophysical and geochemical input variables.
Keywords :
feedforward neural nets; geographic information systems; minerals; terrain mapping; data driven mineral potential mapping; digital data manipulation techniques; feedforward neural network; geochemical input variable; geographic information system; geological input variable; geophysical input variable; gold exploration; high mineral potential areas; map stacking techniques; mineral deposition model; mineral exploration geologists; resource information; Australia; Feedforward neural networks; Feedforward systems; Geographic Information Systems; Geology; Gold; Mineralization; Minerals; Neural networks; Stacking;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223683