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

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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Main Authors: Alessandro Crivellari, Euro Beinat
格式: 文件
语言:English
出版: MDPI AG 2020-12-01
丛编:Mathematics
主题:
deep learning
LSTM
neural networks
traffic forecasting
urban traffic distribution
在线阅读:https://www.mdpi.com/2227-7390/8/12/2233

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https://www.mdpi.com/2227-7390/8/12/2233

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