• DocumentCode
    555517
  • Title

    Analysis on risk status of local government financing platform based on GA-PSO mixed planning algorithm

  • Author

    Li, Kun ; Cao, Wu-jun ; Hu, Xing-wang

  • Author_Institution
    Inst. of Manage. Sci. & Decision, Zhengzhou Univ., Zhengzhou, China
  • Volume
    Part 1
  • fYear
    2011
  • fDate
    3-5 Sept. 2011
  • Firstpage
    47
  • Lastpage
    51
  • Abstract
    With the government´s increasing marketing regulation for real estate and tightening monetary policy, the risk of local government financing platform is increasingly prominent. This paper makes a quantitative analysis for the risk of local government financing platform based on GA-PSO mixed planning algorithm, on the condition that the risk has been qualitatively proved in the educational circles. In this paper, firstly status and cause of risk for the platform, and then GA-PSO mixed planning algorithm is introduced for quantitatively analyses of current situation of the local government financing platform over the country. At last, by analyzing the results, the conclusion is made that the risk of local government financing platform is quite high and measures should be taken immediately for prevention and governance1.
  • Keywords
    genetic algorithms; marketing; particle swarm optimisation; property market; public finance; GA-PSO mixed planning algorithm; educational circles; local government financing platform; marketing regulation; monetary policy; real estate; risk status analysis; Algorithm design and analysis; Genetic algorithms; Indexes; Local government; Planning; Training; Mixed planning algorithm; finance platform; local government; risk;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IE&EM), 2011 IEEE 18Th International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-61284-446-6
  • Type

    conf

  • DOI
    10.1109/ICIEEM.2011.6035102
  • Filename
    6035102