• DocumentCode
    2914935
  • Title

    Study on Agricultural Knowledge Discovery Based on Rough Set Theory

  • Author

    ZhuGe Jianping

  • Author_Institution
    Sch. of Manage., Zhejiang Shuren Univ., Hangzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    701
  • Lastpage
    704
  • Abstract
    Rough set theory has an outstanding advantage in imprecise, uncertain and incomplete information analysis and classification of knowledge acquisition. Upon the characteristics of agricultural knowledge, this paper research theory knowledge discovery methods based on rough set. In this paper, diagnosis of plant diseases and insect pests of agricultural application of knowledge discovery as an example illustrates the feasibility of the method, the data at pre-treatment, the use of genetic algorithm-based attribute reduction, improve search efficiency.
  • Keywords
    agriculture; data mining; genetic algorithms; knowledge acquisition; rough set theory; agricultural knowledge discovery; genetic algorithm-based attribute reduction; information analysis; insect pests; knowledge acquisition; plant diseases; rough set theory; Agriculture; Data mining; Decision making; Fuzzy set theory; Information analysis; Information systems; Knowledge acquisition; Production; Set theory; Uncertainty; agriculture; attribute reduction; knowledge discovery; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.519
  • Filename
    5369295