FCM and graphics technique based method for discontinuities occurrence analysis

To solve the disadvantages of strong subjectivity for traditional plot methods of grouping discontinuities, such as the pole isodensity map and the occurrence rose graph, and the lack of intuitionism for popular clustering methods, this article introduces a plot method called the membership contour map. Based on the data of the membership matrix obtained through the fuzzy C-mean (FCM) algorithm, the membership contour map is realized by a graphics technique. Due to the full use of membership information in FCM clustering, the membership contour map can show the spatial distribution of the membership degree of each clustering, distinguish discontinuities caused by trivial random factors, and read out clustering centers by the scope form from the membership contour map directly. An application of Sanshandao Gold Mine proves that the membership contour map holds the advantages of both intuitionism and objectivity, and can adapt discontinuities data, which do not have obvious dominant groups.