Forecasting Spatially-Distributed Urban Traffic Volumes via Multi-Target LSTM-Based Neural Network Regressor

Monitoring the distribution of vehicles across the city is of great importance for urban traffic control. In particular, information on the number of vehicles entering and leaving a city, or moving between urban areas, gives a valuable estimate on potential bottlenecks and congestions. The possibili...

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Principais autores:	Alessandro Crivellari, Euro Beinat
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2020-12-01
coleção:	Mathematics
Assuntos:	deep learning LSTM neural networks traffic forecasting urban traffic distribution
Acesso em linha:	https://www.mdpi.com/2227-7390/8/12/2233
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