• DocumentCode
    1896569
  • Title

    Application of Support Vector Regression Algorithm in Colleges Recruiting Students Prediction

  • Author

    Ying, E.

  • Author_Institution
    Sch. of Foreign Languages, Harbin Univ. of Sci. & Technol., Harbin, China
  • Volume
    2
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    173
  • Lastpage
    176
  • Abstract
    Support vector regression algorithm is applied to colleges recruiting students prediction in the paper. As colleges recruiting students prediction is a nonlinear regression problem, the input training data of colleges recruiting students are nonlinearly mapped into a high dimensional space in support vector regression model. The amount of colleges recruiting students of Sichuan province from 2000 to 2008 is used to prove the effectiveness of support vector regression method. Then,the forecasting curves of support vector regression method and BP neural network and the comparison of forecasting error for amount of colleges recruiting students between support vector regression method and BP neural network are given in this study.The comparison results of forecasting error for amount of colleges recruiting students between support vector regression method and BP neural network indicate that support vector regression method has a higher forecasting accuracy than BP neural network.
  • Keywords
    backpropagation; educational institutions; forecasting theory; further education; genetic algorithms; regression analysis; support vector machines; BP neural network; Sichuan province; colleges recruiting students prediction; forecasting curves; forecasting error; genetic algorithm; nonlinear regression problem; support vector regression algorithm; Educational institutions; Forecasting; Genetic algorithms; Prediction algorithms; Predictive models; Support vector machines; Vectors; colleges recruiting students; forecasting performance; support vector regression algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-0689-8
  • Type

    conf

  • DOI
    10.1109/ICCSEE.2012.456
  • Filename
    6187928