多元线性回归模型对于空气质量的校准应用研究

A Study on Application of Multiple Linear Regression Model to Air Quality Calibration

自改革开放以来,随着国家经济的快速发展,生态环境遭到一定程度的破坏,空气质量问题也日益严重。本研究聚焦于国控点和自建点大气监测数据进行可视化探索性研究分析,首先以国控点数据为参照对象,以自然因素为变量进行对比分析,研究自然因素对自建点数据的影响。然后分别采用一元线性回归和多元线性回归两种方法对现有的空气质量检测仪存在的问题进行分析,确定各自然因素与空气质量数据的影响程度。最后通过一元和多元线性回归模型模拟分析,校准自建点数据。

Air quality problems have become increasingly serious with the rapid development of the national economy since reform and opening up. This study takes the national control point data as the reference object, and uses natural factors as variables to conduct a comparative analysis to study the influence of natural factors on the self-built point data.Then two methods of unary linear regression and multiple linear regression are used to analyze the existing problems of the existing air quality detectors to determine the degree of influence of various natural factors and air quality data. Through simulation analysis of unary and multiple linear regression models, calibrate the self-built point data.