Abstract
Parametric roll resonance is a ship stability related phenomenon that
generates sudden large amplitude oscillations up to 30-40 degrees of
roll. This can cause severe damage, and it can put the crew in serious
danger. The need for a parametric rolling real time prediction system
has been acknowledged in the last few years. This work proposes a
prediction system based on a multilayer perceptron (MP) neural
network. The training and testing of the MP network is accomplished
by feeding it with simulated data of a three degrees-of-freedom
nonlinear model of a fishing vessel. The neural network is shown to be
capable of forecasting the ship’s roll motion in realistic scenarios.
Original language | English |
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Title of host publication | Proceedings of the Twenty-first International Offshore and Polar Engineering Conference |
Publication date | 2011 |
Pages | 522-529 |
ISBN (Print) | 978-1-880653-96-8 |
Publication status | Published - 2011 |
Event | 21st International Offshore and Polar Engineering Conference - Maui, Hawaii, United States Duration: 19 Jun 2011 → 24 Jun 2011 http://www.isope.org/conferences/conferences.htm |
Conference
Conference | 21st International Offshore and Polar Engineering Conference |
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Country/Territory | United States |
City | Maui, Hawaii |
Period | 19/06/2011 → 24/06/2011 |
Internet address |
Keywords
- Fishing vessels
- Parametric roll
- Artificial neural networks
- Prediction systems