Table of Contents Author Guidelines Submit a Manuscript
Journal of Applied Mathematics
Volume 2014, Article ID 319314, 12 pages
http://dx.doi.org/10.1155/2014/319314
Research Article

A Fast Independent Component Analysis Algorithm for Geochemical Anomaly Detection and Its Application to Soil Geochemistry Data Processing

1Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
2College of Geophysics, Chengdu University of Technology, Chengdu 610059, China

Received 14 March 2014; Revised 21 June 2014; Accepted 7 July 2014; Published 23 July 2014

Academic Editor: Chongbin Zhao

Copyright © 2014 Bin Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A fast independent component analysis algorithm (FICAA) is introduced to process geochemical data for anomaly detection. In geochemical data processing, the geological significance of separated geochemical elements must be explicit. This requires that correlation coefficients be used to overcome the limitation of indeterminacy for the sequences of decomposed signals by the FICAA, so that the sequences of the decomposed signals can be correctly reflected. Meanwhile, the problem of indeterminacy in the scaling of the decomposed signals by the FICAA can be solved by the cumulative frequency method (CFM). To classify surface geochemical samples into true anomalies and false anomalies, assays of the 1 : 10 000 soil geochemical data in the area of Dachaidan in the Qinghai province of China are processed. The CFM and FICAA are used to detect the anomalies of Cu and Au. The results of this research demonstrate that the FICAA can demultiplex the mixed signals and achieve results similar to actual mineralization when 85%, 95%, and 98% are chosen as three levels of anomaly delineation. However, the traditional CFM failed to produce realistic results and has no significant use for prospecting indication. It is shown that application of the FICAA to geochemical data processing is effective.