首页|Simulated-multifractal models: A futuristic review of multifractal modeling in geochemical anomaly classification
Simulated-multifractal models: A futuristic review of multifractal modeling in geochemical anomaly classification
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NSTL
Elsevier
Various statistical methods, including fractal/multifractal techniques, have been applied to clustering of geochemical samples based on their elemental concentrations. Most classification models provide a single classification map whose precision (stability) and accuracy are unknown. Classification models based on more than one approach permit assessment of such uncertainty, but the effect of different assumptions in the model may be difficult to assess. Alternatively, the precision can be assessed using simulation methods on a given modelling approach, such as sequential Gaussian simulation (SGSIM) with a large number of realizations with changes in classification (number of clusters or allocation of samples to specific clusters). In this research, novel robust simulated-multifractal classification models have been introduced and reviewed based on several traditional as well as newly established multifractal models for further consideration in geochemical anomaly classification.