An algorithm for quantifying regionalized ore grades
JOURNAL OF THE SOUTH AFRICAN INSTITUTE OF MINING AND METALLURGY, vol.108, no.2, pp.83-90, 2008 (SCI-Expanded)
- Publication Type: Article / Article
- Volume: 108 Issue: 2
- Publication Date: 2008
- Journal Name: JOURNAL OF THE SOUTH AFRICAN INSTITUTE OF MINING AND METALLURGY
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED)
- Page Numbers: pp.83-90
- Inonu University Affiliated: Yes
Abstract
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).