• DocumentCode
    1791003
  • Title

    Logistic Growth Prediction of B2C E-Commerce Based on Nonlinear Integral

  • Author

    Li Fang-Min ; Huang You-Wen

  • Author_Institution
    Guangzhou Vocational Coll. of Sci. & Technol., Guangzhou, China
  • fYear
    2014
  • fDate
    25-26 Oct. 2014
  • Firstpage
    341
  • Lastpage
    344
  • Abstract
    The precise logistics growth prediction can provide important reference for economic growth and consumer groups. According to the traditional logistics growth prediction method, the ordinary time prediction method was used to predict large deviations, and the result was unstable. So an improved logistic growth prediction of B2C e-commerce was proposed based on nonlinear integral. Firstly, the old data of logistic was analyzed, and then the nonlinear integral approach was used to predict growth of the B2C e-commerce step by step, the accurate logistics growth was achieved. Finally, B2C platform was used to do predict experiment, the result shows that nonlinear integral method can be used in the application, the prediction outcome is stable and reliable, and it has good predictive significance and application value in practice.
  • Keywords
    electronic commerce; logistics; B2C e-commerce; business to customer e-commerce model; electronic commerce; logistics growth prediction; nonlinear integral method; Algorithm design and analysis; Computational modeling; Electronic commerce; Estimation; Logistics; Prediction algorithms; Predictive models; B2C; E-Commerce; Logistics; prediction;
  • 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.2014.89
  • Filename
    7003552