• DocumentCode
    3003051
  • Title

    A real-time prediction system of soil moisture content using genetic neural network based on annealing algorithm

  • Author

    Liang, Ruiyu ; Ding, Yanqiong ; Zhang, Xuewu ; Zhang, Wenchao

  • Author_Institution
    Comput. & Inf. Eng. Coll., Hohai Univ., Changzhou
  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    2781
  • Lastpage
    2785
  • Abstract
    The forecast of soil moisture is the basis of agriculture water-saving irrigation. This paper designs and implements a real-time prediction system of soil moisture based on GPRS and wireless sensor network. Front-end of system uses wireless sensor network to collect moisture data, GPRS network to transmit data; back-end uses genetic BP neural network to analyze and process data, simulated annealing algorithm to optimize result, and gives a real-time prediction. Experimental results show that this system has the advantages of low-cost, high accuracy, convenient maintenance, etc.
  • Keywords
    backpropagation; irrigation; moisture; neural nets; packet radio networks; simulated annealing; soil; wireless sensor networks; GPRS network; agriculture water-saving irrigation; genetic backpropagation neural network; real-time prediction soil moisture content system; simulated annealing algorithm; wireless sensor network; Agriculture; Annealing; Data analysis; Genetics; Ground penetrating radar; Irrigation; Neural networks; Real time systems; Soil moisture; Wireless sensor networks; Annealing algorithm; Genetic algorithm; Real-time prediction; Wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-2502-0
  • Electronic_ISBN
    978-1-4244-2503-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2008.4636647
  • Filename
    4636647