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dc.contributor.authorBrega, JRF-
dc.contributor.authorSoria, MHA-
dc.contributor.authorMarar, João Fernando-
dc.contributor.authorSementille, Antonio Carlos-
dc.contributor.authorRogers, S. K.-
dc.contributor.authorFogel, D. B.-
dc.contributor.authorBezdek, J. C.-
dc.contributor.authorBosacchi, B.-
dc.identifier.citationApplications and Science of Computational Intelligence. Bellingham: Spie-int Soc Optical Engineering, v. 3390, p. 603-611, 1998.-
dc.description.abstractThis paper describes a method for the evaluation of pavement condition through artificial neural networks using the MLP backpropagation technique. Two of the most used procedures for detecting the pavement conditions were applied: the overall severity index and the irregularity index. Tests with the model demonstrated that the simulation with the neural network gives better results than the procedures recommended by the highway officials. This network may also be applied for the construction of a graphic computer environment.en
dc.publisherSpie - Int Soc Optical Engineering-
dc.sourceWeb of Science-
dc.subjectintelligent systempt
dc.subjectartificial neural networkspt
dc.subjectpavement management systempt
dc.titleAn intelligent system for pavement managementen
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUniv Estadual Paulista, Dept Comp, Lab Sistemas Tempo Real, Bauru, SP, Brazil-
dc.description.affiliationUnespUniv Estadual Paulista, Dept Comp, Lab Sistemas Tempo Real, Bauru, SP, Brazil-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofApplications and Science of Computational Intelligence-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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