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Predicting coal mining faults using combined rock relationships
By studying different compressive strengths and changes in the characteristics of rocks,five variables were selected to predict faults in coal mines. Drillholes in the mined area were divided into two populations, i.e., drillholes containing faults and drillholes without faults. Discriminant functio...
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Published in: | Mining science and technology (China) 2009-11, Vol.19 (6), p.745-749 |
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description | By studying different compressive strengths and changes in the characteristics of rocks,five variables were selected to predict faults in coal mines. Drillholes in the mined area were divided into two populations, i.e., drillholes containing faults and drillholes without faults. Discriminant functions were established from the values of the five variables using Fisher's approach. Drillholes in the non-mined areas were allocated to one of the two populations by using discriminant functions. The terrenes of each drillhole were divided into 10 sections, above and below a minable coal seam. Each section has 10 layers of rocks. The population to which each drillhole in a section belongs is sorted out and the probability of each drillhole with faults obtained,i.e., a contour map of predicting the probability of faults in coal mining is shown. A comparison with the real distribution of faults shows that the precision of accurately predicting faults is greater than 70 per cent. |
doi_str_mv | 10.1016/S1674-5264(09)60136-8 |
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Drillholes in the mined area were divided into two populations, i.e., drillholes containing faults and drillholes without faults. Discriminant functions were established from the values of the five variables using Fisher's approach. Drillholes in the non-mined areas were allocated to one of the two populations by using discriminant functions. The terrenes of each drillhole were divided into 10 sections, above and below a minable coal seam. Each section has 10 layers of rocks. The population to which each drillhole in a section belongs is sorted out and the probability of each drillhole with faults obtained,i.e., a contour map of predicting the probability of faults in coal mining is shown. A comparison with the real distribution of faults shows that the precision of accurately predicting faults is greater than 70 per cent.</abstract><pub>Elsevier B.V</pub><doi>10.1016/S1674-5264(09)60136-8</doi><tpages>5</tpages></addata></record> |
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subjects | discriminant analyses geostatistics isoline map of probability mine fault prediction terrain combination 判别函数 岩石层 抗压强度 等值线图 预测精度 |
title | Predicting coal mining faults using combined rock relationships |
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