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dc.contributor.authorLiu, Shukuien_US
dc.contributor.authorXu, Rongen_US
dc.contributor.authorPapanikolaou, Apostolosen_US
dc.identifier.citationLiu, S., Xu, R. & Papanikolaou, A. (2021). Prediction of the motion of a ship in regular head waves using artificial neural networks. 31st International Ocean and Polar Engineering Conference (ISOPE 2021), 1687-1693.en_US
dc.description.abstractThis paper presents a research on the application of artificial neural networks (ANNs) to predict the seakeeping behavior of ships in head waves. The decisive input parameters of the ANNs are identified by analyzing the general equations governing the ship motions. Then, a ship database that considers all major merchant ship types and hull forms is set up and an in-house frequency domain 3D panel method is used to predict the heave and pitch motions of these ships in head waves at typical operational speeds, thus, establishing a motion database, which provides data to train the ANN networks. Several types of neural networks are explored and systematically trained. The developed network is applied to the prediction of the motions of several ships, which are not in the database, to demonstrate their efficiency in quickly and accurately predicting the seakeeping performance of typical merchant ships.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.rights© 2021 International Society of Offshore and Polar Engineers (ISOPE). All rights reserved.en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titlePrediction of the motion of a ship in regular head waves using artificial neural networksen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.conference31st International Ocean and Polar Engineering Conference (ISOPE 2021)en_US
dc.subject.keywordsArtificial Neural Networksen_US
dc.subject.keywordsMulti-Layer Perceptronen_US
dc.subject.keywordsSeakeeping Assessmenten_US
dc.subject.keywordsHeave and Pitchen_US
dc.subject.keywordsHead Wavesen_US
dc.subject.keywordsShip Operationen_US
dc.citation.conferencelocationRhodes, Greece (Virtual)en_US
dc.description.acknowledgementThis research is partly supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (Award Number: #020211-00001; Award Title: “Investigation of the self-propulsion factors for determining minimum propulsion power to ensure safe ship operation at low speeds”).en_US
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