Affiliations: School of Resources and Civil Engineering, Northeastern University, Shenyang, China
Correspondence:
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Corresponding author. Enpu Gong, School of Resourcesand Civil Engineering, Northeastern University, Shenyang, 110004, China. E-mail: enpugong@163.com.
Abstract: Based on the cluster analysis technique, the prediction technology of mineral resources in the mining area is studied and the collected geochemical data are sorted out. Thirty-nine chemical elements of the data are clustered and six relatively stable regions are obtained. Correlation analysis of the geochemical data in four regions is carried out. Through the correlation between the elements and the characteristic elements of each deposit, predicting the possible resources and types in each region, a line chart of the content of 39 elements at different sampling points in each region is drawn. The results of the preliminary prediction and the results of the relevant analysis are combined to obtain the possible resources and resource types of the four regions. Finally, by combining the occurrence environment of each deposit with the geological data of each area, the types of mineral resources and resources in the area are further determined more accurately.
Keywords: Cluster analysis, mineral resources, prediction
