Precise and timely traffic flow prediction holds significant importance in alleviating traffic
congestion. Despite the success of graph convolution traffic flow prediction methods, there is …

Traffic flow prediction is a challenging task in intelligent transportation systems. To improve
the accuracy of traffic flow prediction, graph convolutional neural networks and traffic …

Traffic flow prediction remains an ongoing hot topic in the field of Intelligent Transportation
System. The state-of-the-art traffic flow prediction models can effectively extract both spatial …

As a fundamental technology in the field of intelligent transportation systems, traffic flow
prediction has a wide range of applications. The utilization of Graph Convolutional Network …

An essential component of autonomous transportation system management and decision-
making is precise and real-time traffic flow forecast. Predicting future traffic conditionsis a …

Accurate traffic flow prediction is crucial for the development of intelligent transportation. It
can not only effectively avoid traffic congestion and other traffic problems, but also provide a …

Forecasting traffic flow is significant for intelligent transportation systems (ITS), such as
urban road planning, traffic control, traffic planning, and many more. A flow prediction model …

Deep graph convolution networks (GCNs) have recently shown excellent performance in
traffic prediction tasks. However, they face some challenges. First, few existing models …

Accurate traffic flow prediction is essential to address traffic issues and assist traffic
managers make informed decisions in intelligent transportation systems. Extracting potential …

Traffic flow prediction is an important part of the intelligent transportation system. Accurate
multi-step traffic flow prediction plays an important role in improving the operational …