• DocumentCode
    2088620
  • Title

    Plant Disease Forecasting System Based on Datacollection

  • Author

    Shi, Ming-wang ; Wang, Qing-lian ; Chen, Xi-ling ; Zhai, Ju-Huai ; Deng, Tian-fu ; Kong, Fan-bin ; Li, Xue-yong ; Liu, Qi-Li ; Lang, Jian-Fen

  • Author_Institution
    Henan Inst. of Sci. & Technol., Xinxiang, China
  • fYear
    2009
  • fDate
    20-22 Sept. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    China is one of the countries in the world that suffer serious natural disasters. Frequent and serious biological disasters cause great damage to crop production. The plant disease data of multiform could be analyzed and then a forecasting report was made.This article according to characteristic of the plant disease, introduced forecasts system´s design and key technologies realization based on data mining´s plant disease system. The data mining function may divide into two kinds: Description and forecast. The data mining is a kind of deep level data analysis, it can extract from the mass data has certain rule knowledge, the deep level´s development may further enhance the information resource the use value, the localized data through the data management module data input warehouse, according to the description, the knowledge excavation, finally achieves the forecast the effect. The system collection data management, the report form manufacture and the forecast in windows system.
  • Keywords
    agriculture; crops; data mining; biological disaster; crop production; data collection; data mining; data warehouse; plant disease forecasting system; Crops; Data analysis; Data mining; Diseases; Information resources; Knowledge management; Production; Resource management; System analysis and design; Technology forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science, 2009. MASS '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4638-4
  • Electronic_ISBN
    978-1-4244-4639-1
  • Type

    conf

  • DOI
    10.1109/ICMSS.2009.5301610
  • Filename
    5301610