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
Link To Document :
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