Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/6752
Full metadata record
DC FieldValueLanguage
dc.creatorJoão M. Moreira
dc.creatorJorge Freire de Sousa
dc.creatorAlípio M. Jorge
dc.creatorCarlos Soares
dc.date.accessioned2019-02-02T02:15:30Z-
dc.date.available2019-02-02T02:15:30Z-
dc.date.issued2006
dc.identifier.othersigarra:52665
dc.identifier.urihttps://repositorio-aberto.up.pt/handle/10216/6752-
dc.description.abstractThis paper is about bus trip time prediction in mass transit companies.We describe the motivations to accomplish this task and how it can supportoperational management on such companies. Then, we describe a Data Miningframework that recommends the expected best regression algorithm(s), from anensemble, to predict the duration of a given trip. We present results that show theadvantage of using an ensemble regression approach.
dc.language.isopor
dc.relation.ispartofProceedings of the EWGT2006 joint conferences
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectInteligência artificial, Engenharia, Ciências da computação e da informação
dc.subjectArtificial intelligence, Engineering, Computer and information sciences
dc.titleAn ensemble regression approach for bus trip time prediction
dc.typeArtigo em Livro de Atas de Conferência Internacional
dc.contributor.uportoFaculdade de Economia
dc.contributor.uportoFaculdade de Engenharia
dc.subject.fosCiências exactas e naturais::Ciências da computação e da informação
dc.subject.fosNatural sciences::Computer and information sciences
Appears in Collections:FEP - Artigo em Livro de Atas de Conferência Internacional
FEUP - Artigo em Livro de Atas de Conferência Internacional

Files in This Item:
File Description SizeFormat 
52665.pdf107.47 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons