Evaluation Of Mineral Resources Based On DM And MapGIS

Through the use of data mining techniques combined with MapGIS K9mineralmineral resource evaluation, the traditional evaluation methods, there are some differences,the paper take data mining technology cluster analysis algorithm to identify the occurrenceof target resources using fuzzy resource Type C means clustering and data miningtechniques to clear correlation analysis algorithms occurrence of target.First, the use of MapGIS K9powerful data management capabilities, the study areacollected16kinds of elements,1338preliminary sampling points finishing in the samplingpoints in Poly Analyst object,16kinds of elements measured as a research property, use K-means clustering algorithm to analyze the study area, in order to study thecomprehensiveness, K values taken from3to14, as the study area can be divided intoseven rock, so K clustering <7is not great value, through analysis and comparison, K=8,9,10clustering effect when significant manufacturing zone topology MapGIS K9significant clustering effect in the area, get three regional geochemical anomalies.Second, the data three regional geochemical anomalies were delineated in bothresearch association correlation analysis between the abnormal area elements, thatcombined with the geochemical characteristics of the symbiotic elements came to theconclusion element anomalies area, As, Sb, Hg and Mo association, Ni and W association,Cd and Pb association. Using relevant theories and knowledge of geochemical prospecting,at the same time combining geological lithology characteristics of geochemical elementanomaly area, deduce the region is to look for gold, silver, lead and zinc favourable areas.Third, the data three geochemical anomalies in the area delineated by the Matlab Cprogramming fuzzy clustering analysis, namely the elements as objects, each elementgeochemical data for the property, taking the number of clusters c=4, m=2, ε=0.00001,the element16is part of the analysis to obtain the cluster center4, when the thresholdvalue is selected membership u≥0.35, the first cluster included in the elements, Mo, Cd,Bi, Sb, As, Hg, Au and Ag; The second cluster contains elements Cr, Zn, Mo, Cd, Pb, Bi, As and Ag; third cluster contains the elements Co, Ni, Cu and Sn; s four clusters containelements W. According geochemical theory, reflecting the region’s mine is a gold, silverand polymetallic mineralization zone. Therefore, the region is looking inferred gold, silverand other metal mineral resources favorable location.Comprehensive analysis of correlation analysis, fuzzy clustering results obtained C,combined with the geological characteristics of the study area lithology, indicating that theland is a gold, silver and polymetallic metallogenic.