graph neural networkmethod validationWith the acceleration of urbanization and the continuous growth of transportation demand, the traffic management of smart city road networks has become increasingly complex and critical. Traffic flow prediction, as an important component of smart transportation systems, ...
Traffic Flow Prediction Using Graph Convolution Neural NetworksOC 翻译笔记,程序员大本营,技术文章内容聚合第一站。
To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the macroscopic periodic characteristics of traffic flow,...
Due to the intricate spatial–temporal dependence of traffic flows, especially the hidden dynamic correlations among road nodes, and the dynamic spatial–temporal characteristics of traffic flows, a traffic flow prediction model based on an interactive dynamic spatial–temporal graph convolutional ...
- Spatial temporal factors correlation: Traffic flow in anareawill be affected byitsnearby infrastructures, during specific periods for different areas. You should think about how the volume will change in a specificarea, during a specific time. ...
干什么活:交通流预测(traffic flow forecasting ) 方法:动态图卷积网络(Dynamic Graph Convolutional Network) 创新:通用(Generic) 作者 隔壁北航的大佬们太强了。这个项目有国自然和校级资金支持。 初读 摘要 现存方法的局限性:图卷积网络 共享模式不充分
Due to prediction on the traffic flow is influenced by the real environment and historical data, the produced traffic graph may include significant uncertainty. The graph convolution operation is widely used in traffic flow prediction with its effective modeling ability on graph structures. However, in...
Business location: With the development of smart city, it is more and more popular to leverage find right location to set up a shop or restaurant. Here, one possible solution is based on the crowd flow prediction of regions. Intuitively, the larger the crowd flows are, the better the regio...
Spatial–Temporal Complex Graph Convolution Network for Traffic Flow Prediction 2023, Engineering Applications of Artificial Intelligence Show abstract Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities 2022, Transportation Research Part C: Emerging Technologies Sh...
This repository includes our works on Graph representation learning and its application on Traffic Flow Prediction. The ideas behind our works can be abstracted and demonstrated in the following big picture. All works can be deduced, inspired and created from this picture. ...