Conference
Pattern recognition for imputation of missing radial surface current data - a Malta-Sicily Channel case study
| Τίτλος: | Pattern recognition for imputation of missing radial surface current data - a Malta-Sicily Channel case study |
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| Συγγραφείς: | Ćatipović, Leon, Kalinić, Hrvoje, Matić, Frano, Gauci, Adam, Azzopardi, Joel, 2023 IEEE International Workshop on Metrology for the Sea, Learning to Measure Sea Health Parameters (MetroSea) |
| Στοιχεία εκδότη: | Institute of Electrical and Electronics Engineers |
| Έτος έκδοσης: | 2023 |
| Συλλογή: | University of Malta: OAR@UM / L-Università ta' Malta |
| Θεματικοί όροι: | Remote sensing, Oceanography -- Malta, Operations research -- Case studies, Ocean currents -- Mediterranean Region, Quantitative research -- Evaluation, Oceanography -- Italy -- Sicily |
| Περιγραφή: | Surface currents can accurately be measured remotely using high-frequency radars, with the drawback that those measurements are susceptible to external interference resulting in frequent gaps in data. This paper compares the gap-filling accuracy of four pattern recognition machine learning methods - k-means clustering, self organising maps, growing neural gap and a Generative Adversarial Network. Several experiments are demonstrated using data from Malta-Sicily Channel, exploring the possibilities of applications of feature engineering to reduce the dimensionality of the problem. The methods are also compared to numerical models. Findings indicate how classical pattern recognition algorithms result in an average relative error of around 15%, while the Generative Adversarial Network halved that error. ; peer-reviewed |
| Τύπος εγγράφου: | conference object |
| Γλώσσα: | English |
| Relation: | https://www.um.edu.mt/library/oar/handle/123456789/127325 |
| DOI: | 10.1109/MetroSea58055.2023.10317163 |
| Διαθεσιμότητα: | https://www.um.edu.mt/library/oar/handle/123456789/127325 https://doi.org/10.1109/MetroSea58055.2023.10317163 |
| Rights: | info:eu-repo/semantics/restrictedAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. |
| Αριθμός Καταχώρησης: | edsbas.9EAE09DD |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.1109/MetroSea58055.2023.10317163 |
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