基于时间序列的长沙市PM2.5的统计分析
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引用本文:李 波,朱恩文,冯 倩.基于时间序列的长沙市PM2.5的统计分析[J].经济数学,2017,(1):105-110
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作者单位
李 波,朱恩文,冯 倩 (长沙理工大学 数学与统计学院湖南 长沙 410114) 
中文摘要:通过对长沙市2015年AQI检测指标数值PM2.5与SO2,NO2,PM10,CO,O3间相关性进行分析,得到PM2.5与SO2,NO2,PM10,CO间存在正相关关系,与O3间为负相关关系.后建立自回归移动平均模型(ARMA)对长沙市2015年的PM2.5进行短期预测,得到最优模型为ARMA(3,2).最后对长沙治理PM2.5提出相关建议.
中文关键词:PM2.5;AQI  多元回归模型  ARMA
 
Statistical Analysis of Changsha PM2.5 Based on Time Series
Abstract:PM2.5 gradually becomes the focus of attention. We analyzed the correlation between monitoring index of air pollution PM2.5 and S02,N02,PM10,CO,O3,and found that PM2.5 was associated positively with SO2,NO2,PM10,CO,and negatively with O3.Then through establishing Autoregressive Integrated Moving Average Model(ARMA) to predict the PM2.5 in Changsha,we got ARMA(3,2) is the best .Last, we provide some references to the control of PM2.5 in Changsha.
keywords:PM2.5  AQI  multivariate regression model  ARMA
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