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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods
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Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods

机译：基于不同分层聚类分析方法的水化学分类对比研究

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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.
机译：用于氢化学分析的传统方法是有效但不那么多样化，并且受到限制的物体和条件。鉴于他们的准确性和可靠性差，它们通常用于补充或与其他方法结合使用以解决实际问题。群集分析是一种多元统计技术，可以从复杂数据中提取有用信息。它提供了新的思路和方法，尤其是对地下水的水化学分类。分层集群分析是集群分析中最广泛使用的方法。本研究比较了六个分层聚类分析方法的优缺点，并分析了应用的物体，条件和应用范围。六种方法是：单连杆，完全连杆，中位数联动，质心联动，平均连杆（包括组联动与群内联动），以及病房的最小方差。结果表明，单连杆和完全连杆不适合复杂的实际条件。中位数和质心联动可能导致树木图中的逆转。平均联动通常适用于具有多个样本和大数据的分类任务。然而，沃德的最小方差较少的样品和变量实现了更好的结果。

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