Estimation of Elemental Distributions by Combining Artificial Neural Network and Inverse Distance Weighted (IDW) Based on Lithogeochemical Data in Kahang Porphry Deposit, Central Iran

Abstract

Estimation of elemental distribution basedon geochemical data is important for determinationof elemental prospects in studied areas. The mainaim of this study is to estimate Cu, Mo, Au and Ag with respect to lithogeochemical data in Kahangporphyry deposit, Central Iran, using combinationof Inverse Distance Weighted (IDW) and Artificial Neural Network (ANN). The results obtained by thecombination methods show that the proper elementalanomalies are associated with geological particularsincluding lithological units, alteration zones and faults.Moreover, correlation between raw data and the resultsreveals that the combination method can be applicablefor interpretation of elemental distributions