Combining fuzzy analytic hierarchy process with concentration–area fractal for mineral prospectivity mapping: A case study involving Qinling orogenic belt in central China

We combined cluster analysis, the fuzzy analytic hierarchy process (fuzzy AHP), and the concentration–area (C-A) fractal for mineral prospectivity mapping. First, cluster analysis was used to determine the indicator elements for orogenic Au deposits (omitting redundant geochemical elements). Subsequently, according to pairwise comparisons of mineralization alternatives performed by three exploration experts, a series of fuzzy evaluation matrices were constructed, and the corresponding normalized weights were calculated. Furthermore, on the basis of the multifractal theory, two thresholds for each alternative were obtained (each alternative was divided into a background region, a general anomaly region, and a high anomaly region), and the fuzzy membership function was used to obtain the normalized score of each alternative. Finally, the weight of each alternative was multiplied by the normalized score, and fuzzy superposition was employed to generate a mineralization prediction map, which consisted of high, medium, low, and weak metallogenic potential areas, accounting for 7.05%, 19.67%, 40.99%, and 32.29% of the study area, which contained 4, 1, 1, and 0 of the six known mine occurrences, respectively. The prediction area (P-A) plot indicated that the result predicted 83.3% of Au deposits with an area of 16.7%, indicating that the combination of cluster analysis, the fuzzy AHP, and the concentration–area method is an efficient and economical forecasting method that has guiding significance for mineral prospectivity mapping (MPM). •Cluster analysis has the ability to determine indicator elements.•Fuzzy AHP is useful for MPM in green exploration areas.•The C-A fractal model has advantages over statistical methods for identifying anomalies.•With the three aforementioned methods, the prediction ability reached 83%.