An intelligent system for pavement management

Detalhes bibliográficos
Autor(a) principal: Brega, JRF
Data de Publicação: 1998
Outros Autores: Soria, MHA, Marar, João Fernando [UNESP], Sementille, Antonio Carlos [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1117/12.304849
http://hdl.handle.net/11449/34687
Resumo: This 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.
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spelling An intelligent system for pavement managementintelligent systemartificial neural networkspavement management systemThis 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.Univ Estadual Paulista, Dept Comp, Lab Sistemas Tempo Real, Bauru, SP, BrazilUniv Estadual Paulista, Dept Comp, Lab Sistemas Tempo Real, Bauru, SP, BrazilSpie - Int Soc Optical EngineeringUniversidade Estadual Paulista (Unesp)Brega, JRFSoria, MHAMarar, João Fernando [UNESP]Sementille, Antonio Carlos [UNESP]2014-05-20T15:24:01Z2014-05-20T15:24:01Z1998-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject603-611http://dx.doi.org/10.1117/12.304849Applications and Science of Computational Intelligence. Bellingham: Spie-int Soc Optical Engineering, v. 3390, p. 603-611, 1998.0277-786Xhttp://hdl.handle.net/11449/3468710.1117/12.304849WOS:000073452600062577770513781001912330494844887611882712230914196Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengApplications and Science of Computational Intelligenceinfo:eu-repo/semantics/openAccess2024-04-23T16:11:12Zoai:repositorio.unesp.br:11449/34687Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:17:38.875131Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv An intelligent system for pavement management
title An intelligent system for pavement management
spellingShingle An intelligent system for pavement management
Brega, JRF
intelligent system
artificial neural networks
pavement management system
title_short An intelligent system for pavement management
title_full An intelligent system for pavement management
title_fullStr An intelligent system for pavement management
title_full_unstemmed An intelligent system for pavement management
title_sort An intelligent system for pavement management
author Brega, JRF
author_facet Brega, JRF
Soria, MHA
Marar, João Fernando [UNESP]
Sementille, Antonio Carlos [UNESP]
author_role author
author2 Soria, MHA
Marar, João Fernando [UNESP]
Sementille, Antonio Carlos [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Brega, JRF
Soria, MHA
Marar, João Fernando [UNESP]
Sementille, Antonio Carlos [UNESP]
dc.subject.por.fl_str_mv intelligent system
artificial neural networks
pavement management system
topic intelligent system
artificial neural networks
pavement management system
description This 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.
publishDate 1998
dc.date.none.fl_str_mv 1998-01-01
2014-05-20T15:24:01Z
2014-05-20T15:24:01Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1117/12.304849
Applications and Science of Computational Intelligence. Bellingham: Spie-int Soc Optical Engineering, v. 3390, p. 603-611, 1998.
0277-786X
http://hdl.handle.net/11449/34687
10.1117/12.304849
WOS:000073452600062
5777705137810019
1233049484488761
1882712230914196
url http://dx.doi.org/10.1117/12.304849
http://hdl.handle.net/11449/34687
identifier_str_mv Applications and Science of Computational Intelligence. Bellingham: Spie-int Soc Optical Engineering, v. 3390, p. 603-611, 1998.
0277-786X
10.1117/12.304849
WOS:000073452600062
5777705137810019
1233049484488761
1882712230914196
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Applications and Science of Computational Intelligence
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 603-611
dc.publisher.none.fl_str_mv Spie - Int Soc Optical Engineering
publisher.none.fl_str_mv Spie - Int Soc Optical Engineering
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128341959507968

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