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Soil data clustering by using K-means and fuzzy K-means algorithm

A problem of soil clustering and spatial representation of the obtained results, based on in-situ measurements of physical and chemical characteristics of soil, is analysed in the paper. K-means and fuzzy K-means algorithms are adapted for the soil data clustering. Database of soil samples sampled in Montenegro is used for comparative analysis of the used algorithm. Classified soil data are presented on static Google map.