Back to Search Start Over

Theory and Application of Artificial Neural Networks for the Real Time Prediction of Ship Motion.

Authors :
Khosla, Rajiv
Howlett, Robert J.
Jain, Lakhmi C.
Khan, Ameer
Bil, Cees
Marion, Kaye E.
Source :
Knowledge-Based Intelligent Information & Engineering Systems (9783540288947); 2005, p1064-1069, 6p
Publication Year :
2005

Abstract

Due to the random nature of the ship's motion in an open water environment, the deployment and the landing of vehicles from a ship can often be difficult and even dangerous. The ability to predict reliably 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 for the prediction of ship motion. Two training techniques for the determination of the artificial neural network weights are presented. It is shown that the artificial neural network based on the singular value decomposition produces excellent predictions and is able to predict the ship motion in real time for up to 10 seconds. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540288947
Database :
Supplemental Index
Journal :
Knowledge-Based Intelligent Information & Engineering Systems (9783540288947)
Publication Type :
Book
Accession number :
32914450
Full Text :
https://doi.org/10.1007/11552413_151