| Download | - View author's version: Estimates of wave field in the vicinity of a floating body using its motions and machine learning techniques (PDF, 1.2 MiB)
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| DOI | Resolve DOI: https://doi.org/10.23919/OCEANS44145.2021.9706106 |
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| Author | Search for: Akinturk, Ayhan1; Search for: Zaman, Hasanat1; Search for: Seo, Dong Cheol1; Search for: He, Moqin1; Search for: Mak, Lawrence1 |
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| Affiliation | - National Research Council of Canada. Ocean, Coastal and River Engineering
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| Format | Text, Article |
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| Conference | OCEANS 2021, September 20–23, 2021, San Diego, CA, USA |
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| Subject | wave field estimation; ship motions; machine learning; artificial neural networks; short time FFT |
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| Abstract | Real time estimation of actual and imminent wave fields in the vicinity of ships and floating structures are important for safe and efficient operations. According to the relevant literature, three different approaches have been used practically: the use of wave buoys, ship radars (e.g. X-band and K-band radars) / satellite and ship motions. The present study employs artificial neural networks and machine learning type modelling to extend the previous research on neighboring wave field estimation to consider the relative heading between the ship and the waves. For the different cases evaluated, the proposed machine learning model showed very good prediction for relative heading. Some of the results from this study are presented in this paper. |
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| Publication date | 2021-09-20 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 4d4f5b08-02bc-4a13-b8a0-d58643039dbd |
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| Record created | 2021-09-01 |
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| Record modified | 2022-02-23 |
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