
TY  - JOUR
A1  - Kwan, Karl 
A1  - Reford, Stephen 
A1  - Ma&#xef;ga Abdoul-Wahab, Djiba 
A1  - H. Pitcher, Douglas 
A1  - Bournas, Nasreddine 
A1  - Prikhodko, Alexander 
A1  - Plastow, Geoffrey 
A1  - M. Legault, Jean 
T1  - Supervised Neural Network Targeting and Classification Analysis of Airborne EM, Magnetic and Gamma-ray Spectrometry Data for Mineral Exploration
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2015
VL  - 2015
IS  - 1
SP  - 1
EP  - 5
KW  - 
UR  - https://doi.org/10.1071/ASEG2015AB306 
N2  - The amount of multi-disciplinary (geology, geophysics, remote sensing, etc.) and multi-parameter geophysical (potential field, EM, gamma-ray spectrometry, etc.) data available for mineral exploration is ever increasing. The integration and analysis of the data require effective and efficient search engines or data mining tools. The search engines will take the signatures of known mineral deposits or interpreted mineralization targets (&#34;key words&#34;), search the data space and return potential new targets (&#34;matches&#34;), thus providing locations to the decision makers for follow-up. Two supervised feed-forward multilayer neural network (NN) search algorithms will be presented and analysed. The utility of the NN search tools will be demonstrated with the integration and analysis of airborne electromagnetic (EM), magnetic and radiometric data for mineralization targets in Iullemmeden Basin, Niger. 
ER  -

