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Athanasios Salamanis, Giorgos Margaritis, Dionysios D. Kehagias, Georgios Matzoulas, Dimitrios Tzovaras
Pág. 665 - 674
In this paper we propose a model for accurate traffic prediction under both normal and abnormal conditions. The model is based on the identification of the traffic patterns shown under both normal and abnormal conditions using the density-based clusterin...
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Athanasios Salamanis, Anastasios Drosou, Dimitrios Michalopoulos, Dionysios Kehagias, Dimitrios Tzovaras
Pág. 4552 - 4561
Incidents produce heavy congestion in large urban traffic networks and therefore real time information about them (e.g. location, timestamp, type) can be very useful for the drivers. An efficient way of gathering this type of information is through a cro...
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Kehagias, A. Nicolaou, A. Petridis, V. Fragkou, P.
Pág. 209 - 217
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Kehagias, A. Petridis, V.
Pág. 1432 - 1449
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Petridis, V; Paterakis, E; Kehagias, A
Pág. 862 - 876
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