LSTM-based traffic flow prediction with missing data
Traffic flow prediction plays a key role in intelligent transportation systems. However, since
traffic sensors are typically manually controlled, traffic flow data with varying length, irregular …
traffic sensors are typically manually controlled, traffic flow data with varying length, irregular …
T-LSTM: A long short-term memory neural network enhanced by temporal information for traffic flow prediction
L Mou, P Zhao, H Xie, Y Chen - Ieee Access, 2019 - ieeexplore.ieee.org
Short-term traffic flow prediction is one of the most important issues in the field of intelligent
transportation systems. It plays an important role in traffic information service and traffic …
transportation systems. It plays an important role in traffic information service and traffic …
Traffic flow prediction with long short-term memory networks (LSTMs)
H Shao, BH Soong - 2016 IEEE region 10 conference …, 2016 - ieeexplore.ieee.org
Accurate traffic flow information is crucial for an intelligent transportation system
management and deployment. Over the past few years, many existing models have been …
management and deployment. Over the past few years, many existing models have been …
A hybrid deep learning model with attention-based conv-LSTM networks for short-term traffic flow prediction
Accurate short-time traffic flow prediction has gained gradually increasing importance for
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …
Short-term traffic flow prediction with LSTM recurrent neural network
Accurate and timely short-term traffic flow prediction plays an important role in intelligent
transportation management and control. Traffic flow prediction has a long history and is still …
transportation management and control. Traffic flow prediction has a long history and is still …
Long-term traffic prediction based on lstm encoder-decoder architecture
Z Wang, X Su, Z Ding - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Accurate traffic flow prediction is becoming increasingly important for transportation
planning, control, management, and information services of successful. Numerous existing …
planning, control, management, and information services of successful. Numerous existing …
Short-term traffic flow prediction for urban road sections based on time series analysis and LSTM_BILSTM method
C Ma, G Dai, J Zhou - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
The real-time performance and accuracy of traffic flow prediction directly affect the efficiency
of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of …
of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of …
[HTML][HTML] An autoencoder and LSTM-based traffic flow prediction method
Smart cities can effectively improve the quality of urban life. Intelligent Transportation System
(ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow …
(ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow …
Traffic flow prediction using LSTM with feature enhancement
Long short-term memory (LSTM) is widely used to process and predict events with time
series, but it is difficult to solve exceedingly long-term dependencies, possibly because the …
series, but it is difficult to solve exceedingly long-term dependencies, possibly because the …
[HTML][HTML] Hybrid LSTM neural network for short-term traffic flow prediction
Y Xiao, Y Yin - Information, 2019 - mdpi.com
The existing short-term traffic flow prediction models fail to provide precise prediction results
and consider the impact of different traffic conditions on the prediction results in an actual …
and consider the impact of different traffic conditions on the prediction results in an actual …