Groundwater Quality Assessment: An Improved Approach to K-Means Clustering, Principal Component Analysis and Spatial Analysis: A Case Study

Groundwater Quality Assessment: An Improved Approach to K-Means Clustering, Principal Component Analysis and Spatial Analysis: A Case Study

K-means clustering and principal component analysis (PCA) are widely used in water quality analysis and management. Nevertheless, numerous studies have pointed out that K-means with the squared Euclidean distance is not suitable for high-dimensional datasets. We evaluate a methodology (K-means based...

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Bibliographic Details
Main Authors: Ana Elizabeth Marín Celestino, Diego Armando Martínez Cruz, Elena María Otazo Sánchez, Francisco Gavi Reyes, David Vásquez Soto
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Water
Subjects:
K-means clustering
PCA
spatial analysis
water quality
hydrogeochemical
coastal aquifer
Online Access:http://www.mdpi.com/2073-4441/10/4/437

Internet

http://www.mdpi.com/2073-4441/10/4/437

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