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Application of limited fuzzy clusters to anomaly recognition in complex geological environments
Authors:U. Kramar
Abstract:In stream sediment and soil surveys, samples represent mixtures of components from different geological environments. Such mixed samples are misclassified when using conventional “hard” cluster methods. In fuzzy clustering, each sample is allowed to belong to several clusters. Similar to element concentrations, these cluster contributions can be displayed in contour maps (e.g. kriging maps). The amount of an element that is explained by the cluster contribution and element residuals can be calculated. The modified fuzzy clustering algorithm called “limited fuzzy clusters” used in this paper avoids negative residuals.Stream sediment data of Sierra de San Carlos, Tamaulipas, Mexico are used to demonstrate the possibilities of limited fuzzy clustering in geochemical exploration and mapping. From the different drainage systems, 681 stream sediment samples were taken and analyzed for 24 elements. A nineteen-element data set was used to calculate limited fuzzy clusters and element residuals. The contribution values for the clusters and element residuals are displayed in contour maps. All geological units were outlined by the cluster contributions. Extended anomalies are characterized by their own cluster. Small anomalies are clearly identified from the element residuals.
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