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    Layered ensemble model for short-term traffic flow forecasting with outlier detection

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    Abdullatif_IEEE_conference_paper (387.5Kb)
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    Publication date
    2016-11
    Author
    Abdullatif, Amr R.A.
    Rovetta, S.
    Masulli, F.
    Keyword
    Forecasting
    Predictive models
    Neural networks
    Roads
    Computational modeling
    Data models
    Industries
    Rights
    © 2016 IEEE. Reproduced in accordance with the publisher's self-archiving policy.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Real time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taking into consideration both spatial (road links) and temporal (lag or past traffic flow values) information. We propose a Layered Ensemble Model (LEM) which combines Artificial Neural Networks and Graded Possibilistic Clustering obtaining an accurate forecast of the traffic flow rates with outlier detection. Experimentation has been carried out on two different data sets. The former was obtained from real UK motorway and the later was obtained from simulated traffic flow on a street network in Genoa (Italy). The proposed LEM model for short-term traffic forecasting provides promising results and given the ability for outlier detection, accuracy, robustness of the proposed approach, it can be fruitful integrated in traffic flow management systems.
    URI
    http://hdl.handle.net/10454/17627
    Version
    Accepted manuscript
    Citation
    Abdullatif A, Rovetta S and Masulli F (2016) Layered ensemble model for short-term traffic flow forecasting with outlier detection. In: 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI). 7-9 Sep 2016, Bologna, Italy.
    Link to publisher’s version
    https://doi.org/10.1109/RTSI.2016.7740573
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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