نتایج جستجو برای: Concentration-Number (C-N) Fractal Model
تعداد نتایج: 4700421 فیلتر نتایج به سال:
the aim of this study was to identify various sulfidic mineralized zones in the ghare-tappeh cu deposit (nw iran) based on geo-electrical data including induced polarization (ip) and resistivity (rs) using the concentration-volume (c-v) and number-size (n-s) fractal models. the fractal models were used to separate high and moderate sulfidic zones from low sulfidic zones and barren wall rocks. b...
The purpose of this study is to determine geochemical anomalies on lithogeochemical data from Ardestan area, Central Iran, using concentration-number (C-N) fractal modeling and staged factor analysis. Staged factor analysis is used to the recognition of genetic correlation and elimination of non-indicator elements in three steps. Factor scores of elements were calculated and geochemical data cl...
This study aims to evaluate the efficiency of the concentration-number (C-N) fractal model for discrimination of soil horizon regarding the depth distribution profile. In this regard, soil parameters such as pH, organic carbon content, calcareous mineral content, electrical conductivity and available phosphorus of Ziarat forestland in Golestan Province, north of Iran, has been investigated. The...
In this paper, correlation between rock types and Cu mineralization obtained by Concentration-Number (C-N) fractal model calculated in Kushk-e-Bahram Cu deposit, Central Iran. This deposit is located in the Urumieh-Dokhtar magmatic arc (UDMA). The main subject in this study was determination of relation between the Cu grade populations and rock types based on subsurface data using logratio matr...
Gazestan magnetite-apatite deposit is located in Central Iran and Bafq region, which has been occurred in form of veins, veinlets, and small apatite lenses as well as magnetite in metasomatic rock types such as green chlorite-actinolite rock units. These rocks are situated in the carbonate-volcanic complex of Upper Precambrian-Lower Cambrian Rizo formation. In this study, staged factor analysis...
The aim of this study was to identify various sulfidic mineralized zones in the Ghare-Tappeh Cu deposit (NW Iran) based on geo-electrical data including induced polarization (IP) and resistivity (RS) using the concentration-volume (C-V) and number-size (N-S) fractal models. The fractal models were used to separate high and moderate sulfidic zones from low sulfidic zones and barren wall rocks. B...
The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type and polymetallic mineralization arc. The aim of this study is to identify and subsequently determine geochemical anomalies for exploration of Pb, Zn and Cu mineralization in Mial district situated in UDMA. Factor analysis, Concentration-Number (C-N) fractal model and Local Linear Model Tree (...
In this paper, we aim to present a quantitative modeling for delineating the alteration zones and lithological units in the hypogene zone of Masjed-Daghi Cu-Au porphyry deposit (NW Iran) based on the drill core data. The main goal of this work is to apply Ordinary Kriging (OK) and concentration-volume (C-V) fractal model based on Cu grades in order to separate the different alteration zones and...
The aim of this study is separation of Fe2O3, TiO2 and V2O5 anomalies in Esfordi 1:100,000 sheet which is located in Bafq district, Central Iran. The analyzed elements of stream sediment samples taken in the area can be classified into 5 groups (factors) by factor analysis. The Concentration–Number (C-N) fractal model was used for delineation of the Fe2O3, TiO2 and V2O5 thresholds. According to...
This paper presents a quantitative modeling for delineating alteration zones in the hypogene zone of the Miduk porphyry copper deposit (SE Iran) based on the core drilling data. The main goal of this work was to apply the Ordinary Kriging (OK), Artificial Neural Networks (ANNs), and Concentration-Volume (C-V) fractal modelings on Cu grades to separate different alteration zones. Anisotropy was ...
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