Pages that link to "Item:Q2398596"
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The following pages link to A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration (Q2398596):
Displaying 12 items.
- New indices for characterizing spatial models of Ore deposits by the use of a sensitivity vector and an influence factor (Q883166) (← links)
- Geostatistical simulation of geochemical compositions in the presence of multiple geological units: application to mineral resource evaluation (Q1740326) (← links)
- Three-dimensional prospectivity modeling of Honghai volcanogenic massive sulfide Cu-Zn deposit, eastern Tianshan, northwestern China using weights of evidence and fuzzy logic (Q2022107) (← links)
- Using the graph-cut method to segment the mineralization area in the gejiu region of Yunnan province, China (Q2066825) (← links)
- Identification of mineralization in geochemistry for grid sampling using generalized additive models (Q2066851) (← links)
- An innovative geostatistical sediment trend analysis using geochemical data to highlight sediment sources and transport (Q2130967) (← links)
- Multivariate modelling of the trace element chemistry of arsenopyrite from gold deposits using higher-dimensional algebras (Q2214940) (← links)
- Fusion of geochemical and remote-sensing data for lithological mapping using random forest metric learning (Q2238097) (← links)
- Stochastic modelling of mineral exploration targets (Q2675147) (← links)
- New validity conditions for the multivariate Matérn coregionalization model, with an application to exploration geochemistry (Q2676515) (← links)
- Estimation of potential failure risks in a mine slope using indicator Kriging (Q2854947) (← links)
- A mixed probabilistic-deterministic approach to interpretation of gravity, magnetic, and electric prospecting data (Q2900860) (← links)
