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Telfor Journal
2016, vol. 8, br. 1, str. 56-61
jezik rada: engleski
vrsta rada: neklasifikovan

Soil data clustering by using K-means and fuzzy K-means algorithm
(naslov ne postoji na srpskom)
Faculty of Electrical Engineering Podgorica, University of Montenegro, Podgorica, Montenegro



FORE-MONT - Fostering innovation based research for e-Montenegro (EU-FP7 - 315970)
Project for establishment of pilot Montenegrin Centre of Excellence in Bioinformatics - BIO-ICT (Contract No. 01-1001)


(ne postoji na srpskom)
A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering. A database of soil characteristics sampled in Montenegro is used for a comparative analysis of implemented algorithms. The procedure of setting proper values for control parameters of fuzzy K-means is illustrated on the used database. In addition, validation of clustering is made through visualisation. Classified soil data are presented on the static Google map and dynamic Open Street Map.

Ključne reči

clustering; data mining; K-means; fuzzy Kmeans; pedologic map


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