The running efficiency of forecasting methods is another important concern. To handle this issue, this paper proposes a graph deep learning-based fast traffic flow forecasting method in urban road ...

Traffic flow prediction (TFP) is an very important issue for successfully promoting traffic efficiency and reducing traffic congestion in intelligent transportation system (ITS). In this paper, in ...

To figure these issues out, a novel deep learning traffic flow forecasting framework is proposed in this paper, termed as Ensemble Attention based Graph Time Convolutional Networks (EAGTCN).

This solution is designed to support activities such as network performance monitoring, diagnostics, and traffic flow optimization. The project integrates a simulated network environment (Mininet) to ...

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the climate, and stabilize drones during flight.