• DocumentCode
    478066
  • Title

    Evaluating the Agricultural Information Degree Using a Novel Genetic Algorithm

  • Author

    Liu, Zhibin ; Shen, Peng

  • Author_Institution
    Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding
  • Volume
    1
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    593
  • Lastpage
    596
  • Abstract
    The agricultural information level is on the initial stage in Hebei province, so we should pay more attention to its construction. And on this basis we can find out the influencing factors and corresponding countermeasures. In order to evaluate the agricultural information degree scientifically and accurately, this paper proposes the optimal model based on improved genetic algorithm. The model has the advantages of self-learning, self-organizing and self-adapting, avoids the subjective mistakes in the evaluation process, and improves the evaluating accuracy greatly. The evaluation of 5 cities in Hebei Province shows that the results given by this model are reliable, and this method to evaluate the agricultural information level is feasible.
  • Keywords
    agriculture; genetic algorithms; Hebei province; agricultural information degree; improved genetic algorithm; Analysis of variance; Biological cells; Cities and towns; Computational biology; Evolution (biology); Genetic algorithms; Investments; Power generation economics; Statistics; Synchronous generators; Agricultural information degree; Comprehensive evaluation; Improved genetic algorithm; Indices system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.6
  • Filename
    4666914