印度恒河不同水质数据模式研究:相关与聚类分析

S. Shakhari, A. K. Verma, Debasmita Ghosh, K. Bhar, I. Banerjee
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引用次数: 2

摘要

多年来,对最主要的生命维持资源的日益关注达到了顶点。这项工作旨在使用聚类和相关方法提供数据模式分析。本研究基于分子和非分子水质参数的数据,分析了恒河的水质,用于各种社会工作目的。相关性是有用的,因为它们可以表明一种预测关系,并且基于恒河的理化参数数据,我们可以找到逐年相关矩阵。我们发现了5个簇用于DO、pH和BOD,另外5个簇用于电导率、粪便大肠菌群和总大肠菌群。
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Diverse Water Quality Data Pattern Study of the Indian River Ganga: Correlation and Cluster Analysis
Over the years, the growing concern for the most primary resource of life sustenance is reaching an acme. This work is aimed at providing a data pattern analysis using cluster and correlation methods. This research analyses the water quality of the river Ganga, for the various purposes of social work, based on the data of the molecular and nonmolecular water quality parameters. Correlations are useful because they can indicate a predictive relationship and based on the data of the physio-chemical parameters of the River Ganga, we can find the year-wise correlation matrix. We found five clusters for DO, pH and BOD and another five clusters for Conductivity, Fecal Coliform and Total Coliform.
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