DocumentCode :
3346315
Title :
Ship-motion prediction: algorithms and simulation results
Author :
Zhao, X. ; Xu, R. ; Kwan, C.
Author_Institution :
Intelligent Autom., Inc., Rockville, MD, USA
Volume :
5
fYear :
2004
fDate :
17-21 May 2004
Abstract :
Ship-motion prediction is very useful for several naval operations such as aircraft landing, cargo transfer, off-loading of small boats, and ship "mating" between a big transport ship and some small ships. The prediction information is extremely useful in sea states above 3. Five to ten seconds of ship motion prediction can give the operator ample time to avoid serious collisions. The paper summarizes the development of a high performance ship-motion prediction algorithm using minor component analysis (MCA). Simulation results show that this method can predict ship motion a long time ahead with consistent accuracy. That is, the prediction error is almost the same for the 5 second and 20 second predictions. Other conventional algorithms, such as neural networks (NN), autoregressive methods (AR), and Wiener prediction, were also studied for comparative purposes.
Keywords :
autoregressive processes; neural nets; prediction theory; ships; statistical analysis; 20 sec; 5 sec; Wiener prediction; aircraft landing; autoregressive methods; cargo transfer; minor component analysis; naval operations; neural networks; prediction error; sea states; ship-motion prediction; small boat off-loading; Aircraft; Automation; Boats; Computer crashes; Eigenvalues and eigenfunctions; Marine vehicles; Neural networks; Performance analysis; Prediction algorithms; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8484-9
Type :
conf
DOI :
10.1109/ICASSP.2004.1327063
Filename :
1327063
Link To Document :
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