• DocumentCode
    483216
  • Title

    Study on the Risk Prediction of Real Estate Investment Whole Process Based on Support Vector Machine

  • Author

    Li, Wanqing ; Zhao, Yong ; Meng, Wenqing ; XU, Shipeng

  • Author_Institution
    Sch. of Econ. & Manage., HeBei Univ. of Eng., Handan
  • fYear
    2009
  • fDate
    23-25 Jan. 2009
  • Firstpage
    167
  • Lastpage
    170
  • Abstract
    With the rapid development of real estate, the risk of investment is also increasing rapidly. So the risk of predicting and controlling the real estate investment has become the key to the success or failure of the project. In this paper, a support vector machine (SVM) modeling approach for real estate investment risk prediction is proposed at first, which is made use of its merits of structural risk minimization principle, the small study sample and non-linear to analyze the risk factors during investment every stage in real estate projects, then a model based on support vector machines in real estate investment risk is built up, at last, an example is given to prove that this model is effective and practical. All these are used of providing useful help of the future of real estate investment risk control and management.
  • Keywords
    investment; minimisation; real estate data processing; risk analysis; support vector machines; real estate investment; risk prediction; structural risk minimization principle; support vector machine; Data engineering; Economic forecasting; Engineering management; Investments; Knowledge engineering; Knowledge management; Predictive models; Risk analysis; Risk management; Support vector machines; Fully Mechanized Mining Face; Prediction; Support Vector Machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
  • Conference_Location
    Moscow
  • Print_ISBN
    978-0-7695-3543-2
  • Type

    conf

  • DOI
    10.1109/WKDD.2009.40
  • Filename
    4771904