聚类分析在秦淮河水质指标相关性研究中的应用

随着水质监测尺度和监测网络的扩大,传统的水质指标相关性分析的方法已经不能适应于庞大的水质数据。而采用聚类分析法,在对水质指标进行降维处理的同时,可以筛选出水质相关项。利用SPSS软件计算水质指标相关系数矩阵,并绘制聚类分析树形图,对已知水质数据进行相关性分析,结果发现秦淮河东山站水体总有机碳和高锰酸钾指数、总氮和氨氮具有较强相关性。结合线性回归方程的验证,证明R型聚类分析在庞大数据背景下的水质指标相关性研究中具有较好的效果,可以在水污染治理、水质监测评价中发挥较好的作用。

Application of Cluster Analysis in Correlation Study on Water Quality Indexes

With the enlargement of water quality monitoring scope and network, traditional methods of water quality indexes correlation analysiscan no longer be applicable to a large amount of water quality data. But the cluster analysis method can work it. SPSS software was used to calculatethe correlation coefficient matrix of water quality index with cluster analysis method. And a tree diagram was drawn to analyze the correlation ofwater quality data. It is concluded that the total organic carbon and potassium permanganate index, total nitrogen and ammonia nitrogen have strongcorrelation. Combined with the verification of linear regression, it can be proved that the R cluster analysis has a good effect on the study of waterquality index correlation, and it can play an important role in water pollution control or water quality monitoring and evaluation.