Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks
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...
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| Language: | English |
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MDPI AG
2024-09-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/9/1664 |
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| author | Lúcia Moreira C. Guedes Soares |
| author_facet | Lúcia Moreira C. Guedes Soares |
| author_sort | Lúcia Moreira |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-eb86ce890bd34d52b4821e875cb3ac5d |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-eb86ce890bd34d52b4821e875cb3ac5d2025-08-20T01:55:34ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-09-01129166410.3390/jmse12091664Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural NetworksLúcia Moreira0C. Guedes Soares1Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, PortugalCentre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, PortugalA 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.https://www.mdpi.com/2077-1312/12/9/1664towing tankplanar motion mechanism testsartificial neural networksship’s manoeuvringshallow water |
| spellingShingle | Lúcia Moreira C. Guedes Soares Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks Journal of Marine Science and Engineering towing tank planar motion mechanism tests artificial neural networks ship’s manoeuvring shallow water |
| title | Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks |
| title_full | Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks |
| title_fullStr | Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks |
| title_full_unstemmed | Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks |
| title_short | Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks |
| title_sort | investigation of vessel manoeuvring abilities in shallow depths by applying neural networks |
| topic | towing tank planar motion mechanism tests artificial neural networks ship’s manoeuvring shallow water |
| url | https://www.mdpi.com/2077-1312/12/9/1664 |
| work_keys_str_mv | AT luciamoreira investigationofvesselmanoeuvringabilitiesinshallowdepthsbyapplyingneuralnetworks AT cguedessoares investigationofvesselmanoeuvringabilitiesinshallowdepthsbyapplyingneuralnetworks |