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金属矿山 ›› 2012, Vol. 41 ›› Issue (04): 106-108+143.

• 地质与测量 • 上一篇    下一篇

基于模糊C-means聚类的地球化学数据分析

孟海东1,管世明1,徐贯东2   

  1. 1.内蒙古科技大学矿业工程学院;2.维多利亚大学工程与科学学院
  • 出版日期:2012-04-23 发布日期:2012-04-26
  • 基金资助:

    * 教育部“春晖计划”合作项目 (编号:Z2009-1-01041),内蒙古自治区高等学校科学研究重点项目(编号:NJZZ11140)。

Research of Geochemical Data Processing Based on Fuzzy C-means

Meng Haidong1,Guan Shiming1,Xu Guandong2   

  1. 1.School of Mining Engineering, Inner Mongolia University of Science and Technology;2.School of Engineering and Science, Victoria University
  • Online:2012-04-23 Published:2012-04-26

摘要: 采用数据挖掘技术中模糊C-means聚类算法,以地球化学元素为数据对象、样品分析结果为属性值,对某已知金矿区和锡矿区岩石样品的元素组合特征进行了分析。聚类分析得出的元素组合关系与已知地质资料相一致,表明模糊C-means聚类算法能够客观、有效地发现地球化学元素的组合特征。同时,对位于内蒙古地区某多金属成矿带的地球化学采样数据进行了分析,根据聚类结果推断该地区是寻找金、银多金属矿产资源的目标区域。

关键词: 数据挖掘, 模糊C-means聚类, 地球化学元素, 元素组合特征

Abstract: Combination characteristics of geochemical elements in the known gold ore field and tin ore field are analyzed by means of C-means which takes the geochemical elements as data objects and the sample analysis results as attribute values. The results indicate that C-means clustering algorithm can discover the combination characteristics of geochemical elements objectively and effectively in the given ore fields. At the same time, the combination characteristics of geochemical elements in a geochemical sampling area which is located in a polymetallic metallogenic belt is analyzed. Based on the analyzing result we can deduce that the geochemical sampling area is a target region which is related with gold, silver and polymetallic resources. 

Key words: Data mining, Fuzzy C-means clustering, Geochemical elements, Combination characteristics of elements