Fuzzy c-means and K-means clustering with genetic algorithm for identification of homogeneous regions of groundwater quality

In this study, two different clustering algorithms, fuzzy c -means (FCM) and K -means with genetic algorithm, were used to identify the homogeneous regions in terms of groundwater water quality. For this purpose, data of 14 hydrochemical parameters from 108 wells were sampled in 2016, Golestan provi...

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Veröffentlicht in:	Neural computing & applications Jg. 32; H. 8; S. 3763 - 3775
Hauptverfasser:	Mohammadrezapour, Omolbani, Kisi, Ozgur, Pourahmad, Fariba
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.04.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Chlorine Cluster analysis Clustering Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Electrical resistivity Genetic algorithms Groundwater quality Image Processing and Computer Vision Original Article Parameters Probability and Statistics in Computer Science Quality assessment Sodium Vector quantization Water quality FCM means Iran Piper Clustering Wilcox
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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