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THE NEUTRALIZATION OF SYNGENETIC COMPONENT EFFECT IN STREAM SEDIMENTS GEOCHEMICAL EXPLORATION USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: SHIRINKAND 1:50000 SHEET)

AUTHOR/S: M. AHADI, A.HEZARKHANI
Sunday 1 August 2010 by Libadmin2007

7th International Scientific Conference - SGEM2007, www.sgem.org, SGEM2007 Conference Proceedings/ ISBN: 954-918181-2, June 11-15, 2007

ABSTRACT/Full article not available/

Variability of stream sediment survey data have two principal component
including syngenetic component relates to lithogenesis and lithogeochemical
variation, and epigenetic component relates to mineralization which its
determination is the target in geochemical exploration. In regional stream
sediment surveys, effective lithologic units in syngenetic component are located
in the upstream of related sample. Various methods are used for neutralization
of syngenetic component in stream sediment geochemical surveys such as
lithologic groups separation, principal component analysis, fuzzy logic and
artificial neural network. This paper describes application of comparative
neural network in naturalization of syngenetic component which is very
suitable approach for data clustering. After data clustering by this method
based on rock forming elements and validation of results, 8 optimum clusters
were obtained that indicated lithologic units of survey area, corresponding on
its related geology map. After data normalization of each cluster to its center,
enrichment index data file were compiled, then unielement anomalies were
indicated using computation of average plus standard deviation for enrichment
index data that highlighted abnormal areas.


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