Resumen

TUTMEZ, B.; TERCAN, A.E.  y  KAYMAK, U.. An algorithm for quantifying regionalized ore grades. J. S. Afr. Inst. Min. Metall. [online]. 2008, vol.108, n.2, pp.81-88. ISSN 2411-9717.

We present a novel hybrid algorithm for quantifying the ore grade variability that has central importance in ore reserve estimation. The proposed algorithm has three stages: (1) fuzzy clustering, (2) similarity measure, and (3) grade estimation. The method first considers data clustering, and then uses the clustering information for quantifying the ore grades by means of a cumulative point semimadogram function. The method provides a measure of similarity and gives an indication of the regional heterogeneity. In addition, grade estimations can be obtained at different levels of similarity using a weighting function, which is the standard regional dependence function (SRDF).

Palabras clave : Grade; fuzzy clustering; similarity measure; point madogram; weighting function.

        · texto en Inglés     · Inglés ( pdf )