tWeighting and synthesizing exploration evidence criteria for mineral prospectivity mapping (MPM) areaffected by complexity and ambiguity of ore mineralization processes. In this regard, fuzziness could facil-itate the modeling of such vague processes for MPM. Furthermore, imprecise selection of the explorationcriteria to be used in MPM has negative influence on the efficiency of the generated prospectivity mod-els. In this paper, of various exploration criteria, a coherent set of exploration features were recognizedby using the distance distribution analysis. Then, the application of cosine amplitude-based similarityprocedure was adapted as a data-driven fuzzy logic approach for predictive mapping of porphyry-Cuprospectivity in Arasbaran metallogenic zone, NW Iran. In addition, a conventional data-driven fuzzyprospectivity model was generated for comparison purpose. Comparison of the two models demonstratedthe superiority of the cosine amplitude-based fuzzy procedure for MPM.
