Scholarly record
APPLING FUZZY C-MEANS CLUSTERING TO IDENTIFY ANOMALOUS SAMPLES IN KHOUNI AREA, CENTRAL IRAN
Abstract
Advanced mathematical theories like fuzzy set theory play an increasingly important role in exploration and assessment of mineral deposit. A method based on this theory, Fuzzy C-means Clustering, is presented to determine the background of the elements. In the following research, Fuzzy C-means Clustering (FCMC) method is applied to quantify the lithological background in Khouni Mountain, Central Iran. By applying this method, 254 stream sediment samples classified into 4 clusters according to the membership degree and geology setting. Low geochemical contrasts between the samples minimized the assignment variances by using a fuzzy coefficient of 1.3. The residual components of the elements were interpreted as background. Therefore; the anomalous areas clarified better. The applied method resulted in identifying new anomalous areas and correcting the anomaly locations and grades. Since, Khouni is a poly metallic deposit and well- known as a Cu- Pb- Zn mine; there was an especial aim on the Cu and Zn content. As the result, a new target area found for Cu and Zn anomaly locations of were corrected.
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