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Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem

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dc.affiliation.dptoUC3M. Departamento de Físicaes
dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Sensores Teledetección e Imagen en el Infrarrojoes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorGarcía-Cuesta, Esteban
dc.contributor.authorGalván, Inés M.
dc.contributor.authorCastro González, Antonio Jesús de
dc.date.accessioned2009-06-03T10:00:32Z
dc.date.available2009-06-03T10:00:32Z
dc.date.issued2008-02
dc.description.abstractIn this paper, a combustion temperature retrieval approximation for high-resolution infrared ground-based measurements has been developed based on a multilayer perceptron (MLP) technique. The introduction of a selection subset of features is mandatory due to the problems related to the high dimensionality data and the worse performance of MLPs with this high input dimensionality. Principal component analysis is used to reduce the input data dimensionality, selecting the physically important features in order to improve MLP performance. The use of a priori physical information over other methods in the chosen feature’s phase has been tested and has appeared jointly with the MLP technique as a good alternative for this problem.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationEngineering applications of artificial intelligence Feb 2008, vol. 21, n. 1, p. 26-34
dc.identifier.doi10.1016/j.engappai.2007.03.005
dc.identifier.issn0952-1976
dc.identifier.publicationfirstpage26
dc.identifier.publicationissue1
dc.identifier.publicationlastpage34
dc.identifier.publicationtitleEngineering applications of artificial intelligence
dc.identifier.publicationvolume21
dc.identifier.urihttps://hdl.handle.net/10016/4336
dc.language.isoeng
dc.publisherElsevier
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.engappai.2007.03.005
dc.rights© Elsevier
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.subject.otherCombustions
dc.subject.otherDimensionality reduction
dc.subject.otherGround base remote sensing
dc.subject.otherInverse models
dc.subject.otherNeural networks
dc.subject.otherRetrieval temperature
dc.subject.otherPrincipal component analysis
dc.titleMultilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem
dc.typeresearch article*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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