Grey Relational Analysis In The Evaluation Of Mineral Resources

Grey system theory was established by Julong Deng in1980s. The mainfeature of Grey system theory is less data, poor information and uncertainty. Greyrelational analysis is an important part of gray system theory, which has no strictrequirement of sample size and regular distribution. In recent years, the theory ofgrey system has been developed very rapidly and has been used more and morewidely.Mineral resource plays a very important role in national economy constructionand development. With long-term exploration activities, most of shallow mineraldeposits have been discovered. The exploration becomes more and more difficult sothe aim of the exploration and prospectivity have to become to the conceal deposit.Conceal deposit have limited information, just as a grey system. The grey systemtheory can be an effective method to solve this problem. So this paper mainly usesthe grey system theory for the perspective and assessment of the conceal mineraldeposits.In this study, the grey relational analysis method was used as the theoreticalbasis and GIS ArcGIS Engine10.0and Visual Studio2010was taken as the tools torealize the method. This paper takes Yaojialing Zn-Au polymetallic deposit inTongling as an example, using the grey relational degree algorithm to predict themineral resources for the further exploration. In this paper AE has been used and itcan be summarized as follows:(1) Gridding research area, dividing the study areainto evenly grid surface.(2) Creating the database of geological variability andspatial analysis functions (including intersection overlay, buffer generation, andspatial attributes connection).(3) Realization of the grey relational degreealgorithm and calculation of the associated value.(4) Getting the prospectivitymaps by using the threshold which is calculated by programs.(5) Assessment ofprospectivity area. Finally, this paper compares the spatial coincidence betweenprospectivity area and the known deposits, calculates the coincident degrees, the results are very reasonable which can be used for the further exploration. The studyalso develops a suit of grey relational prediction system for the deposit explorationwhich can be used for the resources perspective and assessment in other deposit ormining area.