| 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,2017,34(1):105-110. |
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| 作者姓名： | 李 波 朱恩文 冯 倩 |
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| 作者单位： | 长沙理工大学 数学与统计学院,湖南 长沙,410114 |
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| 基金项目： | 国家自然科学基金资助项目，湖南省教育厅重点项目，国家级大学生创新创业训练试计划项目 |
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| 摘 要： | 通过对长沙市2015年AQI检测指标数值PM2.5与SO_2,NO_2,PM10,CO,O_3间相关性进行分析,得到PM2.5与SO_2,NO_2,PM10,CO间存在正相关关系,与O_3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.
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| 关 键 词： | PM2.5 AQI 多元回归模型 ARMA |
Statistical Analysis of Changsha PM2.5 Based on Time Series |
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| LI Bo,ZHU En-wen,FENG Qian.Statistical Analysis of Changsha PM2.5 Based on Time Series[J].Mathematics in Economics,2017,34(1):105-110. |
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| Authors: | LI Bo ZHU En-wen FENG Qian |
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| Institution: | (School of Mathematics and Computing Science, Changsha University of Science and Technology, Changsha, Hunan 410114,China) |
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| 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. |
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| Keywords: | PM2 5 AQI multivariate regression model ARMA |
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