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International Journal of Mining and Geo-Engineering، جلد ۵۷، شماره ۴، صفحات ۳۷۳-۳۸۰
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عنوان انگلیسی A Hybrid Fuzzy Ordered Weighted Averaging Method in Mineral Prospectivity Mapping: a case for Porphyry Cu Exploration in Chahargonbad District, Iran
چکیده انگلیسی مقاله This research presents a case study that employs the Fuzzy Ordered Weighted Averaging (FOWA) method to develop mineral prospectivity/potential maps (MPM) for the Chahargonbad district in southeastern Iran. The primary objective of the study is to uncover intricate and concealed relationships between various evidence layers and known ore occurrences through a comprehensive analysis of multi-disciplinary geospatial data. Consequently, thirteen evidence layers were meticulously derived from existing databases, encompassing geological, geochemical, geophysical, and remote sensing data, which were then integrated using the FOWA multi-criteria decision-making approach to delineate favorable zones for porphyry Cu mineralization.
The FOWA methodology employs a diverse array of decision strategies to synthesize input geospatial evidence by incorporating multiple values for an alpha parameter. This parameter serves as the cornerstone of the algorithm, influencing experts' perspectives on MPM risk. The methodology generates seven mineral potential maps to identify the most suitable one(s). By considering a prediction-area plot for data-driven weight assignment to each evidence map, the hybrid FOWA outputs were scrutinized to pinpoint the most appropriate map for targeting significant Cu occurrences. The resulting synthesized evidence map indicates an ore prediction rate of 77%, with known Cu deposits primarily located within favorable zones occupying 23% of the entire district area.
کلیدواژه‌های انگلیسی مقاله Fuzzy ordered weighted averaging, Mineral potential/prospectivity mapping, Evidence layers, Porphyry copper, Chahargonbad
نویسندگان مقاله Shokouh Riahi |
School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Maysam Abedi |
School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Abbas Bahroudi |
School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.

نشانی اینترنتی https://ijmge.ut.ac.ir/article_92107_62b2c880817b09f88a60a7b225894500.pdf
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