Feed-forward and RTRL neural networks for the macroscopic traffic flow prediction and monitoring: the potential of each other
Nadhir Messai, Philippe Thomas, Abdellah El Moudni, Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre · 2004
This paper is about traffic flow short term prediction and monitoring based on magnetic sensors measurements. For these purposes, the advantages and drawbacks of feed-forward and real time recurrent learning neural networks are investigated. Structures determination, weights initialization, networks training and automatic incidents detection are discussed.