On the Determination of the Relative Wave Direction based on Measured Ship Responses using Deep Multi-Task Learning

Malte Mittendorf, Ulrik Dam Nielsen, Harry B. Bingham, Gaute Storhaug

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Abstract

In the present study, a Panamax container vessel sailing in the Northern Atlantic is taken as a case study. Deep neural networks are trained on results of cross-spectral analysis of 6-DOF accelerations to predict significant wave height, peak period, and relative wave direction, which were initially derived from measurements of an X-band wave radar. Both an Inception network and a residual network are compared. Overall, it is found that the vector decomposition of the relative wave heading shows superior prediction accuracy in contrast to other methods from state-of-the-art literature. Several possible extensions of the presented methodology are pointed out.
Original languageEnglish
Title of host publicationProceeding HIPER 2022
EditorsVolker Bertram
Publication date2022
Pages96-106
Publication statusPublished - 2022
Event14th Symposium on High-Performance Marine Vehicles - Cortona, Italy
Duration: 29 Aug 202231 Aug 2022
Conference number: 14
http://data.hiper-conf.info/Hiper2022_Cortona.pdf

Conference

Conference14th Symposium on High-Performance Marine Vehicles
Number14
Country/TerritoryItaly
CityCortona
Period29/08/202231/08/2022
Internet address

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