English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/123571
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Title

Empirical forecasting of HF-radar velocity using genetic algorithms

AuthorsOrfila, Alejandro ; Molcard, Anne; Sayol, Juan Manuel ; Marmain, Julien; Bellomo, Lucio; Quentin, Celine; Barbin, Yves
KeywordsEmpirical modeling
high-frequency radar (HF-Radar)
operational oceanography
Issue Date1-May-2015
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE Transactions on Geoscience and Remote Sensing 53(5): 2875-2886 (2015)
Abstract© 1980-2012 IEEE. We present a coastal ocean current forecasting system using exclusively past observations of a high-frequency radar (HF-Radar). The forecast is made by developing a new approach based on physical and mathematical results of the nonlinear dynamical systems theory that allows to obtain a predictive equation for the currents. Using radial velocities from two HF-Radar stations, the spatiotemporal variability of the fields is first decomposed using the empirical orthogonal functions. The amplitudes of the most relevant modes representing their temporal evolution are then approximated with functions obtained through a genetic algorithm. These functions will be then combined to obtain the hourly currents at the area for the next 36 h. The results indicate that after 4 h and for a horizon of 24 h, the computed predictions provide more accurate current fields than the latest available field (i.e., persistent field).
Publisher version (URL)http://dx.doi.org/10.1109/TGRS.2014.2366294
URIhttp://hdl.handle.net/10261/123571
DOI10.1109/TGRS.2014.2366294
Identifiersdoi: 10.1109/TGRS.2014.2366294
issn: 0196-2892
Appears in Collections:(IMEDEA) Artículos
Files in This Item:
File Description SizeFormat 
IEEE-2015-Empirical-forecasting.pdf4,07 MBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.