Identification of Geochemical Anomalies Using Fractal and LOLIMOT Neuro-Fuzzy modeling in Mial Area, Central Iran

The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type, and polymetallic mineralization arc. In this work, we aim to identify and subsequently determine the geochemical anomalies for exploration of Pb, Zn, and Cu mineralization in the Mial district situated in UDMA. The factor analysis, Concentration-Number (C-N) fractal model, and Local Linear Model Tree (LOLIMOT) algorithm are used for this purpose. The factor analysis is utilized in recognition of the correlation between the elements and their classification. This classified data is used for training the LOLIMOT algorithm based on the relevant elements. The results of the LOLIMOT algorithm represent anomalies in the areas with no lithogeochemical samples, although the C-N log-log plot for target elements are generated based on the stream sediment and lithogeochemical samples, which can be delineated by the mineral potential maps of the target elements. The results obtained by the LOLIMOT and fractal modeling show that the SW and the Eastern parts of the area are proper for further exploration of Cu, Pb, and Zn.