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Journal of Mining and Environment، جلد ۱۶، شماره ۴، صفحات ۱۱۶۵-۱۱۷۸
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عنوان انگلیسی Improving the results of the fractal model of geochemical Mineralization Probability Index Using the Gray Wolf Algorithm on the Stream Sediments Data of Sarduiyeh-Baft Area
چکیده انگلیسی مقاله Discrimination of geochemical anomalies from background is a challenge in that elemental dispersion patterns are affected by a variety of geological factors, which vary from one to another area. While statistical and fractal methods are commonly employed for anomaly detection, they struggle with selecting optimal thresholds. This study proposes the Grey Wolf Optimizer (GWO) algorithm as a novel approach for identifying the optimal boundary between anomalies and background. Stream sediment geochemical data from a copper-mineralized area of the Sarduiyeh-Baft sheets in southeast Iran were utilized for analysis. The Geochemical Mineralization Probability Index (GMPI) was first calculated for Cu-Au, Mo-As, Pb-Zn, and porphyry distributions. Subsequently, fractal methods were used to identify anomalous populations within each GMPI. The GWO algorithm was then applied to these distributions to determine the optimal thresholds. Risk analysis, calculated as the ratio of covered copper occurrences to the covered area, revealed superior reliability for the GWO-derived limit compared to those obtained using fractal methods. For porphyry GMPI values, while the fractal reliability indices are 0.127, 0.44, and 0.5, the GWO limit achieved a value of 0.66. Risk analysis for Cu-Au distribution also caused more desired result for GWO limit rather that fractal ones. This demonstrates the enhanced performance and superior reliability of the GWO algorithm for optimizing anomaly detection thresholds in GMPI data.
کلیدواژه‌های انگلیسی مقاله Geochemical data,Stream sediment,Gray Wolf Optimizer,Anomaly separation
نویسندگان مقاله Kamran Mostafaei |
Department of Mining, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

Mohammad Nabi Kianpour |
School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti Sains Malaysia (USM)

Mahyar Yousefi |
Faculty of Engineering, Malayer University, Malayer, Iran

Meisam Saleki |
School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti Sains Malaysia (USM)

نشانی اینترنتی https://jme.shahroodut.ac.ir/article_3242_d99989267147eeafb94a0d6a91c0ee39.pdf
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