• DocumentCode
    2197713
  • Title

    IBLE Algorithm in Agricultural Disease Diagnosis

  • Author

    Jin HaiYue ; Song Kai

  • Author_Institution
    Sci. & Project Branch, Shenyang Inst. of Technol. Inf., Shenyang, China
  • fYear
    2010
  • fDate
    1-3 Nov. 2010
  • Firstpage
    401
  • Lastpage
    404
  • Abstract
    Although the ID3 algorithm holds the extremely important position in the data mining. But the ID3 algorithm existence cannot process the continual attribute, the computation information gain when the application the deviation in insufficiency and so on selection value many attributes. Therefore, one kind of advanced version decision-making tree algorithm IBLE was proposed that it mainly is uses in the information theory. The channel capacity concept to take chooses the important characteristic to the entity in the measure. Combines the rule with many characteristics the point to distinguish the example can effectively the correct distinction. This article applies this algorithm in the oral cavity disease diagnosis, the experimental result indicated this algorithm has the very strong recognition capability to agriculture case diagnosis to very good assistance diagnosis function.
  • Keywords
    agriculture; crops; data mining; decision making; diagnostic expert systems; IBLE algorithm; ID3 algorithm; agricultural disease diagnosis; computation information gain; data mining; decision-making tree algorithm; diagnostic expert system; field crop disease diagnosis; Data Mining; IBLE algorithm; diagnosing in agriculture disease;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-8548-2
  • Electronic_ISBN
    978-0-7695-4249-2
  • Type

    conf

  • DOI
    10.1109/ICINIS.2010.100
  • Filename
    5693570