• DocumentCode
    2235953
  • Title

    The Application of Grey Correlation Analysis in the Atmospheric Environment Quality Assessment

  • Author

    Liu, Shuliang ; Chi, Xiukai ; Hu, Zhiqiang

  • Author_Institution
    Sch. of Bus. Adm., North China Electr. Power Univ., Baoding, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    3872
  • Lastpage
    3875
  • Abstract
    The gray clustering method is a new clustering method, which is establishment and development on the fuzzy mathematics, it has been widely used in social and economic systems in various fields, and displayed its unique advantages in actual. Gray clustering method is used to conduct environmental quality assessment, which is based on the using the environmental monitoring data, and limited to the spatial and temporal scales, as described in the environmental system is seen as a gray system, and the quality of the environment is affected by a number of factors, some factors are difficult to measure and understand, and some factors have not yet been recognized. Thus, the environmental system can be studied as a gray system. In this paper, the application of gray correlation model of the atmosphere surrounding a power plant to evaluate the quality of the environment.
  • Keywords
    correlation methods; environmental management; fuzzy set theory; grey systems; pattern clustering; atmospheric environment quality assessment; environmental monitoring data; fuzzy mathematics; gray clustering method; grey correlation analysis; spatial scales; temporal scales; Atmospheric measurements; Atmospheric modeling; Clustering methods; Environmental economics; Fuzzy systems; Mathematics; Monitoring; Power generation economics; Power system modeling; Quality assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.1175
  • Filename
    5455660