Recognition and identification of spatial mineralization patterns

A recent development in mineral exploration is the use of information technology to define the distribution of mineralization and prospecting targets using spatial data.With geological, geophysical, and geochemical map layers as input data, fuzzy clustering was used in this study to recognize spatial patterns on the GIS platform, and the mineralization patterns were identified by geological interpretation.Fuzzy clustering is a hybrid spatial pattern recognition method composed of c-means clustering, neural network and fuzzy sets.Being an unsupervised classifier, it uses fuzzy membership as an uncertain measurement of the spatial pattern recognition.In the complex distribution environment where diverse deposit types coexist and intersect, different individualized mineralization patterns can be recognized and identified.This study illustrates the technique of fuzzy clustering spatial mineralization pattern recognition and identification, with successful results, using the 1:200 000 map of Ulanhot, Inner Mongolia as an example.