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 beuseful for operational optimization in mass transit companies and howdata 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 timeover a particular path. We proceed by presenting experimental resultsconducted on real data with the forecasting techniques we found mostadequate, 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://repositorio-aberto.up.pt/handle/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

Files in This Item:
File Description SizeFormat 
63488.pdf135.75 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons