• DocumentCode
    2836442
  • Title

    Forecast and Application of Chinese Automobile Production Based on SVM

  • Author

    Dong, Liangcai ; Xu, Ziqi

  • Author_Institution
    Logistics Eng. Sch., Shanghai Maritime Univ., Shanghai, China
  • fYear
    2011
  • fDate
    17-18 July 2011
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Forecasting techniques are playing an increasingly important role in business decision-making. The study focusing on the forecast of Chinese automobile monthly production will be conducted in this paper. The Forecasting model is designed by using the method of Support Vector Machines, compared with the methods of ARIMA the results show that the SVM model has a more accurate prediction of performance.
  • Keywords
    automobile industry; decision making; support vector machines; Chinese automobile monthly production; SVM; business decision-making; forecasting techniques; support vector machines; Correlation; Forecasting; Kernel; Predictive models; Production; Support vector machines; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits, Communications and System (PACCS), 2011 Third Pacific-Asia Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4577-0855-8
  • Type

    conf

  • DOI
    10.1109/PACCS.2011.5990153
  • Filename
    5990153
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2836442