Performance of a Fuzzy ARTMAP Artificial Neural Network in Characterizing the Wave Regime at the Port of Sines (Portugal)

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dc.contributor.authorSantos, Francisco L.
dc.contributor.authorReis, Maria T.
dc.contributor.authorFortes, Conceicąõ J.E.M.
dc.contributor.authorLotufo, Anna D. [UNESP]
dc.contributor.authorNeves, Diogo R.C.B.
dc.contributor.authorPoseiro, P.
dc.contributor.authorMacIel, Geraldo F. [UNESP]
dc.contributor.institutionCáceres
dc.contributor.institutionNational Laboratory for Civil Engineering (LNEC)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T16:44:37Z
dc.date.available2018-12-11T16:44:37Z
dc.date.issued2016-11-01
dc.description.abstractSantos, F.L.; Reis, M.T.; Fortes, C.J.E.M.; Lotufo, A.D.; Neves, D.R.C.B.; Poseiro, P., and Maciel, G.F., 2016. Performance of a fuzzy ARTMAP artificial neural network in characterizing the wave regime at the Port of Sines (Portugal). Techniques based on artificial neural networks (ANNs) have been increasingly applied to predict emergency situations, such as extreme wave conditions, wave overtopping or flooding, and damage to maritime structures, in coastal and port areas. In this work, a fuzzy adaptive resonance theory with mapping (FAM) ANN was trained to predict the wave regime both inside and at the entrance to the Port of Sines, one of the major trade and economic gateways of the Iberian Peninsula, located on the Portuguese west coast. In situ measurements using pressure sensors, wave buoy data, and results from two numerical wave propagation models-simulating waves nearshore (SWAN) and diffraction refraction elliptic approximation mild slope (DREAMS)-were used to train and validate the ANN. The wave regime was calculated for different points outside and inside the port. In general, the FAM predictions outside the port showed a satisfactory fit to the wave parameters (significant wave height, peak wave period, and mean wave direction) from the numerical model SWAN. Inside the port, differences from the DREAMS model were greater, because the optimized FAM parameters were obtained only for outside the port and the FAM network showed some difficulties in accounting for the complex phenomena of wave refraction, diffraction, and reflection within the port. Consequently, it is of paramount importance to obtain the FAM results based on fully optimized parameters to use the FAM output in place of the numerical models of wave propagation. Nevertheless, this methodology proved capable of providing a fast and satisfactory response that is especially useful in the scope of risk management, particularly in wave forecasting and warning systems.en
dc.description.affiliationUNEMAT Cáceres
dc.description.affiliationHarbours and Maritime Structures Division National Laboratory for Civil Engineering (LNEC)
dc.description.affiliationDepartment of Electric Engineering UNESP
dc.description.affiliationUnespDepartment of Electric Engineering UNESP
dc.format.extent1362-1373
dc.identifierhttp://dx.doi.org/10.2112/JCOASTRES-D-15-00044.1
dc.identifier.citationJournal of Coastal Research, v. 32, n. 6, p. 1362-1373, 2016.
dc.identifier.doi10.2112/JCOASTRES-D-15-00044.1
dc.identifier.issn1551-5036
dc.identifier.issn0749-0208
dc.identifier.scopus2-s2.0-84995480011
dc.identifier.urihttp://hdl.handle.net/11449/169139
dc.language.isoeng
dc.relation.ispartofJournal of Coastal Research
dc.relation.ispartofsjr0,383
dc.relation.ispartofsjr0,383
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.subjectartificial neural network (ANN) training and validation.
dc.subjectin situ measurements
dc.subjectNumerical wave propagation modeling
dc.subjectwave buoy data
dc.titlePerformance of a Fuzzy ARTMAP Artificial Neural Network in Characterizing the Wave Regime at the Port of Sines (Portugal)en
dc.typeArtigo
unesp.author.lattes6022112355517660[4]
unesp.author.orcid0000-0002-0192-2651[4]

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