Applying Data-Driven-Based Logistic Function and Prediction-Area Plot to Map Mineral Prospectivity in the Qinling Orogenic Belt, Central China
نویسندگان
چکیده
This study combines data-driven-based logistic functions with prediction–area (P–A) plot for delineating target areas of orogenic Au deposits in the eastern margin Qinling metallogenic belt, central China. First, appropriate geological and geochemical factors were identified, optimized, transformed into a series fuzzy numbers range 0–1 through function order to determine evidence layer prospecting Au. In addition, P–A was derived on above layers their corresponding overlay pick out proper prediction scheme, process which acidic magmatic activity proved be most important factor ore-controlling. Moreover, further prove advantages this method, traditional linear knowledge-driven approach carried comparative purposes. Finally, based concentration–area (C–A) fractal theory, thresholds determined mineral map generated. The obtained consisted high, medium, low, weak potential areas, accounting 2.5%, 16.1%, 38.4%, 43% area, containing 2, 3, 1, 0 6 known mine occurrences contained, respectively. indicated that result predicted 83% 17% confirming joint application simple, effective, low-cost method prospectivity mapping, can guidance work area.
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ژورنال
عنوان ژورنال: Minerals
سال: 2022
ISSN: ['2075-163X']
DOI: https://doi.org/10.3390/min12101287