• DocumentCode
    1790923
  • Title

    Design of Early Warning System of PM2.5 Detection Based on BP Neural

  • Author

    Zhao Bing-Chen ; Huang Jun-Ying ; Zhang Bin ; Zhang Xiao-Jing

  • Author_Institution
    XingTai Univ., Xingtai, China
  • fYear
    2014
  • fDate
    25-26 Oct. 2014
  • Firstpage
    178
  • Lastpage
    181
  • Abstract
    The issue of PM2.5 is becoming a popular atmospheric research hotpot recently. This particular paper evaluates the era reasons as well as influencing factors associated with PM2.5 based on the information associated with PM2.5 in Xing Tai (2014. 01. 01 - 2014. 04. 26), and builds the actual era as well as evolution mode of PM2.5 in Xing Tai by utilizing evolutionary algorithms formula and BP neuron logical network. Lastly, the actual model´s effectiveness, versatility as well as reliability tend to be validated by experiments.
  • Keywords
    atmospheric composition; atmospheric techniques; neural nets; reliability; PM2.5 BP neuron logical network; PM2.5 detection; PM2.5 evolution mode; XingTai; atmospheric research; early warning system; evolutionary algorithms formula; model effectiveness; reliability; Biological neural networks; Data models; Genetic algorithms; Mathematical model; Neurons; Predictive models; Training; atmospheric research; evolutionary algorithms; neural logical network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-6635-6
  • Type

    conf

  • DOI
    10.1109/ICICTA.2014.50
  • Filename
    7003513