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Group of Marine Dynamics and Hydrodynamics > 2.3 Ship Manoeuvring and Control > Publications
Moreira, L. and Guedes Soares, C. (2023), Simulating Ship Manoeuvrability with Artificial Neural Networks Trained by a Short Noisy Data Set, Journal of Marine Science and Engineering, Vol. 11(1), 15
Artificial Neural Networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with a scale model. This work aims to evaluate the performance of ship manoeuvrability models developed by applying Artificial Neural Networks. These models are trained with a very small quantity of noisy data from zig zag and circle experiments, carried out in agreement with the IMO standards. As a consequence of the small dimensions of the ship model, the wind effect is evident in some of the recorded experiments. A neural network model was trained to forecast zig zags and circle manoeuvres. The results obtained show very good accuracy both in the prediction of the speed of referred manoeuvres.
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