B. Shokouh Saljoughi
Department of Mining and Metallurgy Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
[ 1 ] - A comparison between knowledge-driven fuzzy and data-driven artificial neural network approaches for prospecting porphyry Cu mineralization; a case study of Shahr-e-Babak area, Kerman Province, SE Iran
The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become a high priority in this region. Different direct and indirect methods try to predict promising a...
[ 2 ] - A comparative study of fractal models and U-statistic method to identify geochemical anomalies; case study of Avanj porphyry system, Central Iran
The most significant aspect of a geochemical exploration program is to define and separate the anomalous values from the background. In the past decades, geochemical anomalies have been identified by means of various methods. Most of the conventional statistical methods aiming at defining the geochemical concentration thresholds for separating anomalies from the background have limited the effi...
[ 3 ] - Identification of geochemical anomalies associated with Cu mineralization by applying spectrum-area multi-fractal and wavelet neural network methods in Shahr-e-Babak mining area, Kerman, Iran
The Shahr-e-Babak district, as the studied area, is known for its large Cu resources. It is located in the southern side of the Central Iranian volcano–sedimentary complex in SE Iran. Shahr-e-Babak is currently facing a shortage of resources, and therefore, mineral exploration in the deeper and peripheral spaces has become a high priority in this area. This work aims to identify the geochemical...
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