Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods
Bibliographic Data
| ID | 15512160 |
|---|---|
| Authors | Jianwei Bu (0000-0002-3511-7140, Ministry of Natural Resources), Wei Liu (0000-0002-5949-0302, China University of Geosciences, corresponding author), Zhao Pan (0000-0001-9602-432X, China University of Geosciences), Kang Ling (China University of Geosciences) |
| Year | 2020 |
| Volume | 17 |
| Issue | 24 |
| Pages | 9515-9515 |
| Publication date | 2020-12-18 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph17249515 |
| PMID | 33353090 |
| OpenAlex | W3112524779 |
| Language | EN |
| Citations received | 2 |
| References cited | 33 |
Traditional methods for hydrochemical analyses are effective but less diversified, and are constrained to limited objects and conditions. Given their poor accuracy and reliability, they are often used in complement or combined with other methods to solve practical problems. Cluster analysis is a multivariate statistical technique that extracts useful information from complex data. It provides new ideas and approaches to hydrogeochemical analysis, especially for groundwater hydrochemical classification. Hierarchical cluster analysis is the most widely used method in cluster analysis. This study compared the advantages and disadvantages of six hierarchical cluster analysis methods and analyzed their objects, conditions, and scope of application. The six methods are: The single linkage, complete linkage, median linkage, centroid linkage, average linkage (including between-group linkage and within-group linkage), and Ward's minimum-variance. Results showed that single linkage and complete linkage are unsuitable for complex practical conditions. Median and centroid linkages likely cause reversals in dendrograms. Average linkage is generally suitable for classification tasks with multiple samples and big data. However, Ward's minimum-variance achieved better results for fewer samples and variables
Biology · Centroid · Cluster (spacecraft · Cluster analysis · Complete linkage · Data mining · Dendrogram · Hierarchical clustering · Linkage (software · Multivariate statistics · Statistics · Computer Science · Groundwater and Isotope Geochemistry · Groundwater and Watershed Analysis · Mathematics · Medicine · Water Quality and Pollution Assessment · Artificial Intelligence · Genetics
| Citations per year | 0.67 |
|---|---|
| Citation span | 2023 - 2024 (2) |
| Highly cited | No |