自建点空气质量数据校准的一种数学模型

A Mathematical Model for Data Calibration of Self-built Point Air Quality

随着城市化进程的加快及人们生活水平的不断提高,人们对空气质量问题越来越关注,文章用EXCEL表的数据分析功能对2019年全国大学生建模竞赛D题的附件1和附件2所给数据进行分析,发现空气质量指标主要是由PM2.5、PM10及O 3提供,附件2自建点数据与附件1国控点数据具有相关性。用多元线性回归的方法,将附件1国控点的相应数据作为因变量,附件2自建点对应数据作为自变量,建立了6个多元回归方程用来校正自建点“两尘四气”的数据。

With the acceleration of urbanization and the continuous improvement of people’s living standards,people have paid more and more attention to air quality problems.This paper uses the data analysis function of Excel table to make an analysis of the data given in Appendix 1 and Appendix 2 of the National Undergraduate Modeling Competition D in 2019.It is found that the air quality indicators are mainly provided by PM2.5,PM10 and O 3,and the self-built point data in Appendix 2 and the national control point data in Appendix 1 are correlated with each other.By using multiple linear regression,the corresponding data of national control points in Appendix 1 is taken as the dependent variable,and the corresponding data of self built points in Appendix 2 is taken as the independent variable,six multiple regression equations are established to correct the data of“two dust and four gas”of self-built points.