Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction
As a core technology of Intelligent Transportation System, traffic flow prediction has a wide
range of applications. The fundamental challenge in traffic flow prediction is to effectively …
range of applications. The fundamental challenge in traffic flow prediction is to effectively …
Pre-training enhanced spatial-temporal graph neural network for multivariate time series forecasting
Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications.
Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly …
Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly …
Decoupled dynamic spatial-temporal graph neural network for traffic forecasting
We all depend on mobility, and vehicular transportation affects the daily lives of most of us.
Thus, the ability to forecast the state of traffic in a road network is an important functionality …
Thus, the ability to forecast the state of traffic in a road network is an important functionality …
Learning dynamics and heterogeneity of spatial-temporal graph data for traffic forecasting
Accurate traffic forecasting is critical in improving safety, stability, and efficiency of intelligent
transportation systems. Despite years of studies, accurate traffic prediction still faces the …
transportation systems. Despite years of studies, accurate traffic prediction still faces the …
Spatial-temporal identity: A simple yet effective baseline for multivariate time series forecasting
Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications.
Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly …
Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly …
Hierarchical spatio–temporal graph convolutional networks and transformer network for traffic flow forecasting
Graph convolutional networks (GCN) have been applied in the traffic flow forecasting tasks
with the graph capability in describing the irregular topology structures of road networks …
with the graph capability in describing the irregular topology structures of road networks …
Spatio-temporal hierarchical MLP network for traffic forecasting
Traffic forecasting is an indispensable part of intelligent transportation systems. However,
existing methods suffer from limited capability in capturing hierarchical temporal …
existing methods suffer from limited capability in capturing hierarchical temporal …
Learning all dynamics: Traffic forecasting via locality-aware spatio-temporal joint transformer
Forecasting traffic flow and speed in the urban is important for many applications, ranging
from the intelligent navigation of map applications to congestion relief of city management …
from the intelligent navigation of map applications to congestion relief of city management …
Multispans: A multi-range spatial-temporal transformer network for traffic forecast via structural entropy optimization
Traffic forecasting is a complex multivariate time-series regression task of paramount
importance for traffic management and planning. However, existing approaches often …
importance for traffic management and planning. However, existing approaches often …
Multi-scale spatial-temporal aware transformer for traffic prediction
R Tian, C Wang, J Hu, Z Ma - Information Sciences, 2023 - Elsevier
Traffic prediction is an important part of smart city management. Accurate traffic prediction
can be deployed in urban applications such as congestion alerting and route planning, thus …
can be deployed in urban applications such as congestion alerting and route planning, thus …