{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T06:18:52Z","timestamp":1774333132050,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T00:00:00Z","timestamp":1671667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the European Regional Development Fund","award":["02\/SAICT\/032037\/2017"],"award-info":[{"award-number":["02\/SAICT\/032037\/2017"]}]},{"name":"the European Regional Development Fund","award":["UIDB\/UIDP\/00134\/2020"],"award-info":[{"award-number":["UIDB\/UIDP\/00134\/2020"]}]},{"name":"the Portuguese Foundation for Science and Technology","award":["02\/SAICT\/032037\/2017"],"award-info":[{"award-number":["02\/SAICT\/032037\/2017"]}]},{"name":"the Portuguese Foundation for Science and Technology","award":["UIDB\/UIDP\/00134\/2020"],"award-info":[{"award-number":["UIDB\/UIDP\/00134\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMSE"],"abstract":"<jats:p>Artificial neural networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with a scaled model. This work aims to evaluate the performance of the proposed method of training the artificial neural network model even with a very small quantity of noisy data. The data used for the training consisted of zig-zag and circle manoeuvres carried out in agreement with the IMO standards. The wind effect is evident in some of the recorded experiments, creating additional disturbance to the fitting scheme. The method used for the training of the network is the Levenberg\u2013Marquardt algorithm, and the results are compared with the scaled conjugate gradient method and the Bayesian regularization. The results obtained with the different methodologies show very suitable accuracy in the prediction of the referred manoeuvres.<\/jats:p>","DOI":"10.3390\/jmse11010015","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T01:42:13Z","timestamp":1671759733000},"page":"15","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Simulating Ship Manoeuvrability with Artificial Neural Networks Trained by a Short Noisy Data Set"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5284-182X","authenticated-orcid":false,"given":"L\u00facia","family":"Moreira","sequence":"first","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8570-4263","authenticated-orcid":false,"given":"C.","family":"Guedes Soares","sequence":"additional","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,22]]},"reference":[{"key":"ref_1","first-page":"191","article-title":"Controllability","volume":"Volume 3","author":"Lewis","year":"1989","journal-title":"Principles of Naval Architecture"},{"key":"ref_2","first-page":"283","article-title":"Measurement of hydrodynamic characteristics from ship maneuvring trials by system identification","volume":"88","author":"Abkowitz","year":"1980","journal-title":"SNAME Trans."},{"key":"ref_3","first-page":"97","article-title":"Measurements of ship resistance, powering and maneuvering coefficients from simple trials during a regular voyage","volume":"96","author":"Abkowitz","year":"1988","journal-title":"Trans. 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