• DocumentCode
    1748874
  • Title

    Forecasting the population of the corn earworm Helicoverpa zea

  • Author

    Elgaddel, Nazik ; Lin, Frank C. ; Nobakht, Manocher ; Okunbor, Daniel

  • Author_Institution
    Dept. of Math. & Comput. Sci., Maryland Univ., Princess Anne, MD, USA
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2316
  • Abstract
    The corn earworm (CEW) is significant pest for major crops such as soybean and corn. An accurate forecast of its population will be of great benefit to farmers, who must allocate a correct percentage of their land to trap crops. We apply statistical and neural network methods to estimate future populations based upon historical data
  • Keywords
    agriculture; autoregressive moving average processes; forecasting theory; neural nets; time series; Helicoverpa zea; corn earworm; neural network methods; pest control; pest population forecasting; statistical methods; time series; trap crops; Africa; Agriculture; Computer science; Crops; Europe; Neural networks; Pest control; Smoothing methods; South America; Temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.938530
  • Filename
    938530