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Application of Dempster-Shafer theory in mineral resource potential mapping
Authors:CHEN Yong-liang  WU Wei  LI Xue-bin
Abstract:The Dempster-Shafer theory has been successfully applied to mineral resource potential mapping in GIS environmental. In this applied form, basic probability assignment and combined basic probability assignment are applied to measuring map pattern and map pattern combination, respectively; and the environment composed of the only two singleton sets (deposit set and non-deposit set), is used for expressing the entire map area. For a subarea in which the certain map pattern combination exists, the combined basic probability assignment corresponding to the map pattern combination existing in this subarea, expresses the belief of inferring the subarea belonging to the deposit set from the evidence that the corresponding map pattern combination existing in the subarea. Thus, it may be served as a statistical index measuring the relative mineral resource potentials of the subarea. And it may be determined like 1) dividing the map area into a series of small equal-sized grid cells and then select the training sample set composed of the well-known grid cells or the entire grid cells; 2) estimating the basic probability assignments corresponding to each map pattern fromthe training sample set; 3) determining the map pattern combination existing in each cell, and then appling the Dempster's Rule of Combination to integrating the all basic probability assignments corresponding to the map patterns existing in the cell into the combined basic probability assignment. Mineral resource potential mapping with the Dempster-Shafer theory is demonstrated on a case study to select mineral resource targets. The experimental results manifest that the model can be compared with the weights of evidence model in the effectiveness of mineral resource target selection.
Keywords:environment  Dempster-Shafer theory  basic probability assignment  combined basic probability assignment  mineral resource  mineral target selection
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