• DocumentCode
    2066547
  • Title

    Ship motion prediction for launch and recovery of air vehicles

  • Author

    Khan, Ameer ; Bil, Cees ; Marion, Kaye E.

  • Author_Institution
    Sch. of Aerosp., Manuf. & Mech. Eng., RMIT Universit, Melbourne, Vic., Australia
  • fYear
    2005
  • fDate
    2005
  • Firstpage
    2795
  • Abstract
    Due to the random nature of the ship´s motion in an open water environment, the deployment and the landing of air vehicles from a ship can often be difficult and even dangerous. The ability to reliably predict the motion will allow improvements in safety on board ships and facilitate more accurate deployment of vehicles off ships. This paper presents an investigation into the application of artificial neural network methods trained using singular value decomposition and genetic algorithms for the prediction of ship motion. It is shown that the artificial neural network produces excellent predictions and is able to predict the ship motion satisfactorily for up to 7 seconds.
  • Keywords
    genetic algorithms; military computing; military vehicles; neural nets; path planning; ships; singular value decomposition; 7 sec; air vehicle launch; air vehicle recovery; artificial neural network; genetic algorithm; open water environment; ship motion prediction; singular value decomposition; Accuracy; Aircraft; Artificial neural networks; Australia; Autoregressive processes; Helicopters; Marine vehicles; Missiles; Trajectory; Vehicle safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    OCEANS, 2005. Proceedings of MTS/IEEE
  • Print_ISBN
    0-933957-34-3
  • Type

    conf

  • DOI
    10.1109/OCEANS.2005.1640198
  • Filename
    1640198