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A spatial data mining method for mineral resources potential assessment

机译:矿产资源潜力评估的空间数据挖掘方法

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On the basis of multi-source geology spatial database and traditional spatial data mining, a spatial data mining method for mineral resources potential assessment was proposed in this paper, which the spatial characteristics and uncertainty of geology data were reasonable to consider. The method mainly include continuous geological spatial data discretization, spatial relationship abstracting and attribute transforming, mining metallogenic association rules and quality assessment, comprehensive evaluation of metallogenic association rules and potential assessment. Finally, the experiment of mineral potential assessment for iron deposits was performed in Eastern Kunlun, Qinghai province, China, using spatial data mining method and weights-of-evidence model, respectively. The results indicate that the prediction accuracy of spatial data mining was obvious higher than weights-of-evidence model's, the method is suitable for mineral resources potential assessment and its effectiveness is good.
机译:在多源地质空间数据库和传统空间数据挖掘的基础上,本文提出了一种用于矿产资源潜在评估的空间数据挖掘方法,其空间特征和地质数据的不确定性是合理的。该方法主要包括连续地质空间数据离散化,空间关系抽象和属性转化,采矿成矿协会规则和质量评估,综合评价矿物学关联规则和潜在评估。最后,利用空间数据挖掘方法和权重模型,在中国青海省东昆仑矿矿床矿物潜力评估实验。结果表明,空间数据采矿的预测精度明显高于证据模型的重量,该方法适用于矿产资源潜在评估,其有效性是好的。

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