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...

Full description

Saved in:
Bibliographic Details
Published in:Telfor Journal Vol. 8; no. 1; pp. 56 - 61
Main Authors: Hot, Elma, Popovic-Bugarin, Vesna
Format: Journal Article
Language:English
Published: Telecommunications Society, Academic Mind 2016
Subjects:
clustering
data mining
fuzzy K-means
K-means
pedologic map
ISSN:1821-3251
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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