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ORCID: https://orcid.org/0000-0002-4030-6907, Martínez González, Sergio
ORCID: https://orcid.org/0000-0002-7322-5898 and Castro Fernández, Rosa María de
ORCID: https://orcid.org/0000-0002-2143-1155
(2025).
An Artificial Neural Network-Based Approach for Instantaneous Estimation of the Sea Surface Elevation in a Wave Farm.
"IEEE Access", v. 13
;
pp. 181088-181099.
ISSN 2169-3536.
https://doi.org/10.1109/ACCESS.2025.3622308.
| Título: | An Artificial Neural Network-Based Approach for Instantaneous Estimation of the Sea Surface Elevation in a Wave Farm |
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| Autor/es: |
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| Tipo de Documento: | Artículo |
| Título de Revista/Publicación: | IEEE Access |
| Fecha: | 16 Octubre 2025 |
| ISSN: | 2169-3536 |
| Volumen: | 13 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Accuracy; Arrays; Artificial neural network; Control strategies; Data models; Delay control systems; Estimation; Forecasting; Identification; Low-pass filters; Network-based approach; Neural networks; Power; Power converters; Prediction; Prediction systems; Predictive models; Recurrent neural networks; Sea measurements; Sea surface; Sea surface elevation; Surface waters; Surface waves; Time delay; Time delay neural network; Timing circuits; Wave energy conversion; Wave energy converter; Wave estimation; Wave farm; Wave power; Wave predictions |
| Escuela: | E.T.S.I. Industriales (UPM) |
| Departamento: | Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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Many control strategies to maximise the captured power by wave energy converters depend on the knowledge of the incoming wave in a short term future. However, the wave prediction may be unpractical in a wave farm, since many measurement systems would be required. As a part of a prediction system, this paper presents an estimator of the instantaneous sea surface elevation in an open-field sea area for potential wave farm deployment based on a single measurement point. The approach is based on a time delay artificial neural network and the paper explores the performance of the estimation for a given field and the sensitivity to different sea characteristics. The proposed realisation of the artificial neural network is found to be accurate and robust, resulting in a useful tool for a wave prediction system in a farm for control purposes.
| ID de Registro: | 93540 |
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| Identificador DC: | https://oa.upm.es/93540/ |
| Identificador OAI: | oai:oa.upm.es:93540 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/10402143 |
| Identificador DOI: | 10.1109/ACCESS.2025.3622308 |
| URL Oficial: | https://ieeexplore.ieee.org/document/11205511 |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 30 Ene 2026 13:34 |
| Ultima Modificación: | 30 Ene 2026 13:34 |
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