• DocumentCode
    2543063
  • Title

    Study of afforestation design based on association rules

  • Author

    Shan Yao ; Zhongke Feng

  • Author_Institution
    Comput. & Inf. Eng., Beijing Univ. of Agric., Beijing, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1555
  • Lastpage
    1558
  • Abstract
    In order to improve the accuracy of forest decision-making and design the technical measures for the forest types, tree species, planting density, planting mixing and afforestation methods technically and economically. This paper adopts data mining technique based on association rules to analysis the relevance among specification of soil preparation, planting spacing and the ratio of mixing plantation, and discovers the afforestation knowledge from afforestation survey design data. This research realizes the support to afforestation decision analysis by using association rules, and provides the reference for the afforestation decision support.
  • Keywords
    data mining; decision support systems; forestry; vegetation; afforestation decision support; afforestation knowledge discovery; afforestation survey design data; association rules; data mining technique; forest decision-making; forest types; mixing plantation ratio; planting density; planting mixing; planting spacing specification; soil preparation specification; technical measures; tree species; Algorithm design and analysis; Association rules; Databases; Forestry; Soil; Vegetation; Afforestation design; Association rules; Data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6233832
  • Filename
    6233832