Journals Information
Universal Journal of Geoscience(CEASE PUBLICATION) Vol. 3(2), pp. 59 - 65
DOI: 10.13189/ujg.2015.030203
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Estimation of Elemental Distributions by Combining Artificial Neural Network and Inverse Distance Weighted (IDW) Based on Lithogeochemical Data in Kahang Porphry Deposit, Central Iran
Reza Karami 1,*, Peyman Afzal 1,2
1 Department of Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 Camborne School of Mines, University of Exeter, Penryn, UK
ABSTRACT
Estimation of elemental distribution based on geochemical data is important for determination of elemental prospects in studied areas. The main aim of this study is to estimate Cu, Mo, Au and Ag with respect to lithogeochemical data in Kahang porphyry deposit, Central Iran, using combination of Inverse Distance Weighted (IDW) and Artificial Neural Network (ANN). The results obtained by the combination methods show that the proper elemental anomalies are associated with geological particulars including lithological units, alteration zones and faults. Moreover, correlation between raw data and the results reveals that the combination method can be applicable for interpretation of elemental distributions.
KEYWORDS
Grade Estimation, Artificial Neural Network, Inverse Distance Weighted (IDW), Kahang Porphyry Deposit
Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Reza Karami , Peyman Afzal , "Estimation of Elemental Distributions by Combining Artificial Neural Network and Inverse Distance Weighted (IDW) Based on Lithogeochemical Data in Kahang Porphry Deposit, Central Iran," Universal Journal of Geoscience(CEASE PUBLICATION), Vol. 3, No. 2, pp. 59 - 65, 2015. DOI: 10.13189/ujg.2015.030203.
(b). APA Format:
Reza Karami , Peyman Afzal (2015). Estimation of Elemental Distributions by Combining Artificial Neural Network and Inverse Distance Weighted (IDW) Based on Lithogeochemical Data in Kahang Porphry Deposit, Central Iran. Universal Journal of Geoscience(CEASE PUBLICATION), 3(2), 59 - 65. DOI: 10.13189/ujg.2015.030203.