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

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 Monten...

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Vydáno v:Telfor Journal Ročník 8; číslo 1; s. 56 - 61
Hlavní autoři: Hot, Elma, Popovic-Bugarin, Vesna
Médium: Journal Article
Jazyk:angličtina
Vydáno: Telecommunications Society, Academic Mind 2016
Témata:
clustering
data mining
fuzzy K-means
K-means
pedologic map
ISSN:1821-3251
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Shrnutí: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.
ISSN:1821-3251
DOI:10.5937/telfor1601056H