Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit, NW Iran
Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit, NW Iran
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DOI：
10.1007/s11053-015-9271-2
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发表时间：
2016-06-01
影响因子：
5.4
通讯作者：
Carranza, Emmanuel John M.
中科院分区：
文献类型：
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作者：
Geranian, Hamid;Tabatabaei, Seyed Hassan;Carranza, Emmanuel John M.
在这篇论文中，我们使用判别分析（DA）和支持向量机（SVM），结合表层土壤地球化学异常和早期钻孔数据，对伊朗西北部Sari-Gunay金矿进行了地下金矿化建模。其中70%的数据作为训练数据，其余30%作为测试数据。在临界值（0.5 g/t）以上用克里格法得到的块体品位之和乘以块体厚度，作为产能指数（PI）。然后，利用分形方法将PI变量分为背景、中等和高三类。利用训练土壤地球化学数据，计算了支持向量机和数据分析方法的4种分类函数。同时，利用各种地球化学资料和分类功能，预测了金矿化带的总体扩展范围。利用Sari-Gunay山的矿产预测模型，分别定位了高潜力区和中等潜力区，进行了进一步的系统钻探和侦察钻探。Agh-Dagh山和Sari-Gunay和Agh-Dagh山之间地区的这些模型用于确定中等和高潜力地区，以便进一步进行侦察钻探。结果表明，nu-SVM和c-SVM分别以73.8%和72.3%的准确率优于数据分析方法。
In this contribution, we used discriminant analysis (DA) and support vector machine (SVM) to model subsurface gold mineralization by using a combination of the surface soil geo-chemical anomalies and earlier bore data for further drilling at the Sari-Gunay gold deposit, NW Iran. Seventy percent of the data were used as the training data and the remaining 30 % were used as the testing data. Sum of the block grades, obtained by kriging, above the cutoff grade (0.5 g/t) was multiplied by the thickness of the blocks and used as productivity index (PI). Then, the PI variable was classified into three classes of background, medium, and high by using fractal method. Four classification functions of SVM and DA methods were calculated by the training soil geochemical data. Also, by using all the geochemical data and classification functions, the general extension of the gold mineralized zones was predicted. The mineral prediction models at the Sari-Gunay hill were used to locate high and moderate potential areas for further infill systematic and reconnaissance drilling, respectively. These models at Agh-Dagh hill and the area between Sari-Gunay and Agh-Dagh hills were used to define the moderate and high potential areas for further reconnaissance drilling. The results showed that the nu-SVM method with 73.8 % accuracy and c-SVM with 72.3 % accuracy worked better than DA methods.