Traffic flow prediction is a fundamental problem in transportation modeling and
management. Many existing approaches fail to provide favorable results due to being: 1) …

Accurate and timely traffic flow information is important for the successful deployment of
intelligent transportation systems. Over the last few years, traffic data have been exploding …

Traffic flow prediction is an essential part of the intelligent transport system. This is the
accurate estimation of traffic flow in a given region at a particular interval of time in the future …

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 flow prediction has received extensive attention recently, since it is a key step to
prevent and mitigate traffic congestion in urban areas. However, most previous studies on …

Deep neural networks (DNNs) have recently demonstrated the capability to predict traffic
flow with big data. While existing DNN models can provide better performance than shallow …

Traffic flow prediction plays an indispensable role in the intelligent transportation system.
The effectiveness of traffic control and management relies heavily on the prediction …

Instability is a common problem in deep belief network–back propagation forecasting model,
and the trend of traffic data will affect the forecasting results of the model. Therefore, this …

The timely access to accurate traffic data is essential to the development of intelligent traffic
systems. However, the existing traffic prediction methods cannot achieve satisfactory results …

In this modern era, traffic congestion has become a major source of severe negative
economic and environmental impact for urban areas worldwide. One of the most efficient …