Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/6752Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | João M. Moreira | |
| dc.creator | Jorge Freire de Sousa | |
| dc.creator | Alípio M. Jorge | |
| dc.creator | Carlos Soares | |
| dc.date.accessioned | 2019-02-02T02:15:30Z | - |
| dc.date.available | 2019-02-02T02:15:30Z | - |
| dc.date.issued | 2006 | |
| dc.identifier.other | sigarra:52665 | |
| dc.identifier.uri | https://repositorio-aberto.up.pt/handle/10216/6752 | - |
| dc.description.abstract | This 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.iso | por | |
| dc.relation.ispartof | Proceedings of the EWGT2006 joint conferences | |
| dc.rights | openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Inteligência artificial, Engenharia, Ciências da computação e da informação | |
| dc.subject | Artificial intelligence, Engineering, Computer and information sciences | |
| dc.title | An ensemble regression approach for bus trip time prediction | |
| dc.type | Artigo em Livro de Atas de Conferência Internacional | |
| dc.contributor.uporto | Faculdade de Economia | |
| dc.contributor.uporto | Faculdade de Engenharia | |
| dc.subject.fos | Ciências exactas e naturais::Ciências da computação e da informação | |
| dc.subject.fos | Natural 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 | |
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