Back to Search Start Over

Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks

Authors :
Lúcia Moreira
C. Guedes Soares
Source :
Journal of Marine Science and Engineering, Vol 12, Iss 9, p 1664 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

A set of planar motion mechanism experiments of the Duisburg Test Case Post-Panamax container model executed in a towing tank with shallow depth is applied to train a neural network to analyse the ability of the proposed model to learn the effects of different depth conditions on ship’s manoeuvring capabilities. The motivation of the work presented in this paper is to contribute an alternative and effective approach to model non-linear systems through artificial neural networks that address the manoeuvring simulation of ships in shallow water. The system is developed using the Levenberg–Marquardt backpropagation training algorithm and the resilient backpropagation scheme to demonstrate the correlation between the vessel forces and the respective trajectories and velocities. Sensitivity analyses were performed to identify the number of layers necessary for the proposed model to predict the vessel manoeuvring characteristics in two different depths. The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.

Details

Language :
English
ISSN :
20771312
Volume :
12
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Journal of Marine Science and Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.b86ce890bd34d52b4821e875cb3ac5d
Document Type :
article
Full Text :
https://doi.org/10.3390/jmse12091664