• DocumentCode
    3773974
  • Title

    Agricultural Economic Evaluation Based on Improved Support Vector Regression

  • Author

    Min Huang

  • Author_Institution
    Qinhai Univ., China
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    118
  • Lastpage
    121
  • Abstract
    The essence of agricultural project bid is a high-dimensional nonlinear space mathematical optimization problem. In order to improve the generalization performance of SVR algorithm, intelligent algorithm is used to train the SVR parameters, which can make the parameters of SVR optimal. The improved support vector regression evaluation model is applied to the bidding area of agricultural project. The success of some project in some agricultural company proves the reliability and enforceability of the model. The improved model reduces the influence of human factors to improve the objectivity and impartiality of evaluation results.
  • Keywords
    "Support vector machines","Companies","Kernel","Optimization","Genetic algorithms","Economics","Training"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2015 8th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICICTA.2015.38
  • Filename
    7473250