An Analysis of the Use of Predictive Modeling with Business Intelligence Systems for Exploration of Precious Metals Using Biogeochemical Data

Thomas A. Woolman and John C. Yi
Additional contact information
Thomas A. Woolman: On Target Technologies, Amissville, VA, USA
John C. Yi: Department of Decision and System Sciences, Saint Joseph’s University, Philadelphia, PA, USA

International Journal of Business Intelligence Research (IJBIR), 2013, vol. 4, issue 2, 39-53

Abstract: This study addresses the use of predictive modeling techniques; primarily feed-forward artificial neural networks as a tool for forecasting geological exploration targets for gold prospecting. It also provides evidence of effectiveness of using Business Intelligence systems to model pathfinder variables, anomaly detection, and forecasting to locate potential exploration sites for precious metals. The results indicate that the use of advanced Business Intelligence systems can be of extremely high value to the extractive minerals exploration industry.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jbir.2013040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jbir00:v:4:y:2013:i:2:p:39-53

Access Statistics for this article

International Journal of Business Intelligence Research (IJBIR) is currently edited by Ana Azevedo

More articles in International Journal of Business Intelligence Research (IJBIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().