• DocumentCode
    1752768
  • Title

    Crop Disease Dynamic Forecast Integrated with Case-based Reasoning Methodology

  • Author

    Yang, Zhengang ; Luo, Yanhui ; Deng, Feiqi ; Li, Ling

  • Author_Institution
    Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    2551
  • Lastpage
    2554
  • Abstract
    Taking cucumber downy mildew (CDM) as research object, this research explores a technology of crop disease dynamic forecast integrated with case-based reasoning (CBR) methodology. A case indexing mechanism guided by idea of vantage case is developed to speed up the retrieval process and rapidly generate a similar case set for a new case in this CBR system. The range of optimal cluster number for this application is determined through the analysis and comparison between the exhaustive search and the search using proposed indexing mechanism. The precision and recall evaluations are conducted for each testing case using the X fold cross-validation approach, the reasoning effectiveness employing different thresholds of dissimilarity distance (TDD) is figured out and the optimal TDD for this CBR system is determined
  • Keywords
    case-based reasoning; crops; diseases; forecasting theory; X fold cross-validation approach; case-based reasoning; crop disease dynamic forecast; cucumber downy mildew; exhaustive search; optimal TDD; optimal cluster number; thresholds of dissimilarity distance; Automation; Crops; Diseases; Educational institutions; Indexing; Pathogens; Plants (biology); Protection; System testing; Technology forecasting; CBR; Clustering; Crop disease; Forecast;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1712822
  • Filename
    1712822