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Adarules: Learning rules for real-time road-traffic prediction

Autor
Mena-Yedra, R.; Gavaldà, R.; Casas, J.
Tipus d'activitat
Article en revista
Revista
Transportation Research Procedia
Data de publicació
2017-12-17
Volum
27
Pàgina inicial
11
Pàgina final
18
DOI
https://doi.org/10.1016/j.trpro.2017.12.106 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/114367 Obrir en finestra nova
URL
https://www.sciencedirect.com/science/article/pii/S2352146517310037 Obrir en finestra nova
Resum
Traffic management is being more important than ever, especially in overcrowded big cities with over-pollution problems and with new unprecedented mobility changes. In this scenario, road-traffic prediction plays a key role within Intelligent Transportation Systems, allowing traffic managers to be able to anticipate and take the proper decisions. This paper aims to analyze the situation in a commercial real-time prediction system with its current problems and limitations. We analyze issues relat...
Citació
Mena-Yedra, R., Gavaldà, R., Casas, J. Adarules: Learning rules for real-time road-traffic prediction. "Transportation research procedia", 17 Desembre 2017, vol. 27, p. 11-18.
Paraules clau
Adaptation to change, Autolearning, Real-time traffic prediction
Grup de recerca
LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge

Participants

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