摘要
以成都市2019年全年的PM2.5、气温、可吸入颗粒物PM10和一氧化碳CO的基本监测指标数据为研究对象,利用MATLAB分析PM2.5与其他几组数据的关系。由建立的多元线性回归模型可知,温度对PM2.5的影响不显著,可吸入颗粒物PM10和一氧化碳CO对PM2.5有重要影响。对所得模型进行t检验并改进模型,预测成都市未来PM2.5为增长趋势。
Through regarding the basic monitoring index data of PM2.5,temperature,inhalable particle PM10 and CO in Chengdu City in 2019 as the research objects,the research analyzes the relationship between PM2.5 and data of other groups by MATLAB.From the multi linear regression model,we find that temperature has no significant effect on PM2.5,and inhalable particle PM10 and CO have important effect on PM2.5.The t-test is carried out to improve the model,and the improved regression model is used to predict the growth trend of PM2.5 in Chengdu City.
作者
徐东
杨晓芳
Xu Dong;Yang Xiaofang(College of Mathematics,Chengdu Normal University,Chengdu 611130,China)
出处
《黑龙江科学》
2021年第6期36-37,共2页
Heilongjiang Science
基金
成都师范学院省级大学生创新项目“基于SDIR模型PM2.5的影响因素探究”(S202014389088)。