• DocumentCode
    3222803
  • Title

    Multiple regression analysis on causes of urban fog-haze in China-based on data mining

  • Author

    Xiaoning Yue ; Zhaojia Meng ; Zhonghu Yuan

  • Author_Institution
    Coll. of Normal, Shenyang Univ., Shenyang, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    4408
  • Lastpage
    4413
  • Abstract
    The article discussed the causes of urban fog-haze based on grey system theory. Introduced concept of meteorological effect function and non-meteorological effect function, combined with multiple regression theory and data mining, multiple mixed effect model was established. This model involved fog-haze intensity with the meteorological effect and the non-meteorological effect. The contribution rate of secondary aerosols was calculated, it solved "virtual-high" measurement of secondary aerosols when the relative humidity was higher. Through correlation analysis on PM10 and meteorological effect, the article established that meteorological effect played a key role in intensity change of foghaze. By Residual analysis on the model, the reliability and accuracy of the model was proved.
  • Keywords
    aerosols; air pollution; atmospheric humidity; data mining; environmental science computing; fog; grey systems; meteorology; regression analysis; visibility; China; correlation analysis; data mining; fog-haze intensity; grey system theory; meteorological effect function; multiple mixed effect model; multiple regression analysis; multiple regression theory; relative humidity; residual analysis; secondary aerosols; urban fog-haze cause; virtual-high measurement; Aerosols; Correlation; Data models; Humidity; Indexes; Nitrogen; Causes; Effect function; Fog-haze; Multiple Regression; Secondary aerosols;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162651
  • Filename
    7162651