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Journal of the Southern African Institute of Mining and Metallurgy

On-line version ISSN 2411-9717
Print version ISSN 0038-223X

J. S. Afr. Inst. Min. Metall. vol.108 n.2 Johannesburg Feb. 2008




An algorithm for quantifying regionalized ore grades



B. TutmezI; A.E. TercanII; U. KaymakIII

IInonu University, Department of Mining Engineering, Malatya, Turkey
IIHacettepe University, Department of Mining Engineering, Ankara, Turkey
IIIErasmus University Rotterdam, Econometric Institute, Rotterdam, The Netherlands




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).

Keywords: Grade, fuzzy clustering, similarity measure, point madogram, weighting function



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Paper received Dec. 2006
Revised paper received Jan. 2008

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