摘要
查阅了全国各地区的污水排放总量及主要污染物的排放数据发现,废水的污染物组成大体可以分为两部分,一类是混合型污染物如石油类等,另一类是重金属元素如重金属“砷”,经过典型相关分析的计算,发现这两类污染物存在相伴相依的关系,如化学需氧量污染物就含有多种其他变量相关,于是构造了多元线性模型,分析这些主要污染物之间存在的多元线性关系,并计算相关关系的大小,通过模型检验和诊断构造正确的回归模型,最终可以得出化学需氧量和氨氮等变量有相关关系,根据相关关系的大小和正负,最后对这些主要污染物进行解释并提出相应的建议。
After consulting the data of the total amount of sewage discharged and the main pollutants dis-charged in different regions of the country, it is found that the pollutant composition of wastewater can be divided into two parts, one is mixed pollutants such as petroleum, the other is heavy metal elements such as “Arsenic”. Through the calculation of canonical correlation analysis, the two kinds of pollutants are found to have a concomitant and interdependent relationship. For instance, chemical oxygen demand pollutants contain many other variables, so a multivariate linear model is constructed to analyze the multivariate linear relationship between these main pollutants, and calculate the size of the correlation relationship. Through model testing and diagnosis, a correct regression model is constructed, and ultimately a multivariate linear model can be obtained. Chemical oxygen demand and ammonia nitrogen are correlated. According to the magnitude of positive or negative correlation, the main pollutants are explained and some suggestions are put forward.
出处
《统计学与应用》
2019年第5期734-743,共10页
Statistical and Application
