Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/6750| Author(s): | João M. Moreira Alípio Jorge Jorge Freire de Sousa Carlos Soares |
| Title: | A data mining approach for trip time prediction in mass transit companies |
| Issue Date: | 2005 |
| Abstract: | In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and how data mining techniques can be used to improve results. Firstly, we an- alyze which departments need trip time prediction and when. Secondly, we review related work and thirdly we present the analysis of trip time over a particular path. We proceed by presenting experimental results conducted on real data with the forecasting techniques we found most adequate, and conclude by discussing guidelines for future work. |
| Subject: | Tecnologia dos transportes, Engenharia electrotécnica, electrónica e informática Transport technology, Electrical engineering, Electronic engineering, Information engineering |
| Scientific areas: | Ciências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática Engineering and technology::Electrical engineering, Electronic engineering, Information engineering |
| URI: | https://hdl.handle.net/10216/6750 |
| Source: | Proceedings of the workshop W11 on Data Mining for Business |
| Document Type: | Artigo em Livro de Atas de Conferência Internacional |
| Rights: | openAccess |
| License: | https://creativecommons.org/licenses/by-nc/4.0/ |
| Appears in Collections: | FEUP - Artigo em Livro de Atas de Conferência Internacional |
This item is licensed under a Creative Commons License
