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Publications
Moreira, L. and Guedes Soares, C. (2024), Investigation of vessel manoeuvring abilities in shallow depth applying Neural Networks, Journal of Marine Science and Engineering, Vol. 12, 1664
A set of Planar Motion Mechanism (PMM) experiments of the Duisburg Test Case (DTC) 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 of learning the effects of different depth conditions on ship’s manoeuvring capabilities. The system is developed employing the LevenbergMarquardt 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 capability of 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 the prediction of ship manoeuvring varying the depth in shallow water.
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