%0 Journal Article
%T The usefulness of cluster analysis in the analysis of data obtained in the monitoring of the water environment
%A Kubala, Marek
%J Technical Transactions
%V 2017
%R 10.4467/2353737XCT.17.218.7761
%N Volume 12 Year 2017 (114)
%P 181-189
%K water environment monitoring, cluster analysis, hierarchical clustering, k-means clustering
%@ 0011-4561
%D 2017
%U https://ejournals.eu/en/journal/czasopismo-techniczne/article/the-usefulness-of-cluster-analysis-in-the-analysis-of-data-obtained-in-the-monitoring-of-the-water-environment
%X 
	Data obtained through the monitoring of the water environment often includes a number of indicators, and is frequently collected from a large area or over a long period of time. Analysis of such data can be problematic. The division of elements which have a certain degree of similarity into subgroups may facilitate data analysis and provide indications as to the direction of the analysis. One tool for the separation of such groups of similar elements is cluster analysis. This paper describes the two most commonly used cluster analysis algorithms and summarises the results of several applications of cluster analysis in water monitoring.