Deep learning has achieved good performance in short-term traffic forecasting recently.
However, the stochasticity and distribution imbalance are main characteristics to traffic flow …

Short‐term traffic forecast is one of the essential issues in intelligent transportation system.
Accurate forecast result enables commuters make appropriate travel modes, travel routes …

Accurate forecasting of future traffic flow has a wide range of applications, which is a
fundamental component of intelligent transportation systems. However, timely and accurate …

Accurate traffic flow prediction is becoming increasingly important for transportation
planning, control, management, and information services of successful. Numerous existing …

Traffic congestion is a thorny issue to many large and medium-sized cities, posing a serious
threat to sustainable urban development. Recently, intelligent traffic system (ITS) has …

Accurate short-time traffic flow prediction has gained gradually increasing importance for
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …

Timely and accurate traffic flow forecasting is open challenging. Canonical long short-term
memory (LSTM) network is considered qualified to capture the long-term temporal …

Short-term traffic flow prediction plays an important role in intelligent transportation system.
Numerous researchers have paid much attention to it in the past decades. However, the …

To reduce the increasingly congestion in cities, it is essential for intelligent transportation
system (ITS) to accurately forecast the short-term traffic flow to identify the potential …

Deep learning approaches have reached a celebrity status in artificial intelligence field, its
success have mostly relied on Convolutional Networks (CNN) and Recurrent Networks. By …