Trip time prediction in mass transit companies. A machine learning approach

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2005

Autores

João M. Moreira (Autor) FEUP; Alípio Jorge (Autor) FEUP; Jorge Freire de Sousa (Autor) FEUP; Carlos Soares (Autor) FEUP

Ata de Conferência Internacional

Título: Advanced OR and AI methods in transportation

Páginas: 276-283

EURO working group in transportation

Poznan, 13-16 Septembet 2005

Classificação Científica

CORDIS: Ciências Tecnológicas > Engenharia

Outras Informações

Abstract (EN): In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and which machine learning techniques can be used to improve results. Firstly, we analyze 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8