Open AccessCalibration of Air Quality Data Based on Multiple Regression Model
Author(s) -
Hanping Zhang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/514/3/032048
Subject(s) - regression analysis , linear regression , calibration , air quality index , statistics , gray (unit) , quality (philosophy) , computer science , environmental science , meteorology , mathematics , geography , philosophy , epistemology , medicine , radiology
According to the data of question D’s Annex 1 and Annex 2 of the National University Student Modeling Contest 2019, the correlation between the 6 air quality data errors and 5 meteorological factors at the self-built station is obtained by using the gray correlation method. Using the multiple linear regression method,and making the difference between the air quality data of the self-built station and the national control station as the dependent variable, and the meteorological data of the self-built station as the independent variables, six multiple regression equations were established to correct the air quality data of the self-built station.