H. Azizi
School of Electrical Engineering and Computer Sciences, University of North Dakota, Grand Forks, North Dakota, USA.
[ 1 ] - Bayesian Data Fusion: a Reliable Approach for Descriptive Modeling of Ore Deposits
Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, in current paper are just concentrations of indicated elements, were collected from Angouran’s ...
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