• DocumentCode
    2862375
  • Title

    Research on Intelligent Auto-Generating Test Paper Based on Improved Genetic Algorithms

  • Author

    Wu Xiaoqin ; Song Yin

  • Author_Institution
    Key Lab. of Network & Intell. Inf. Process., Hefei Univ., Hefei, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The constraint conditions of the auto-generating test paper are analyzed. The mathematical model of intelligence test paper generation system is set up and a new method of composing test paper based on the improved genetic algorithm is given. The result of the experiments shows that the new method is more efficient and easier to deal with the problem of autogenerating test paper than the traditional algorithms. Autogenerating test paper has the advantages of high success rate and fast speed, and better performance and practicability.
  • Keywords
    educational administrative data processing; genetic algorithms; auto generating test paper constraint condition; improved genetic algorithm; intelligent auto generating test paper; Algorithm design and analysis; Convergence; Genetic algorithms; Information analysis; Information processing; Intelligent networks; Laboratories; Mathematical model; Microelectronics; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5366125
  • Filename
    5366125