In this paper we show a hybrid modeling approach which combines Artificial Neural Networks and a simple statistical approach in order to provide a one hour forecast of urban traffic flow rates. Experimentation has been carried out on three different classes of real streets and results show that the proposed approach outperforms the best of the methods it puts together. © 2015 Elsevier B.V.

Urban traffic flow forecasting through statistical and neural network bagging ensemble hybrid modeling

Pizzuti, S.
2015

Abstract

In this paper we show a hybrid modeling approach which combines Artificial Neural Networks and a simple statistical approach in order to provide a one hour forecast of urban traffic flow rates. Experimentation has been carried out on three different classes of real streets and results show that the proposed approach outperforms the best of the methods it puts together. © 2015 Elsevier B.V.
Neural networks;Bagging;Traffic flow forecasting;Ensembling
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/2374
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