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SOTA
交通预测
Traffic Prediction On Pemsd8
Traffic Prediction On Pemsd8
评估指标
12 steps MAE
12 steps RMSE
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
12 steps MAE
12 steps RMSE
Paper Title
Repository
STG-NCDE
15.45
24.81
Graph Neural Controlled Differential Equations for Traffic Forecasting
STG-NRDE
15.32
24.72
Graph Neural Rough Differential Equations for Traffic Forecasting
HAGCN
14.85
-
HAGCN : Network Decentralization Attention Based Heterogeneity-Aware Spatiotemporal Graph Convolution Network for Traffic Signal Forecasting
-
DDGCRN
14.40
-
A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting
-
PDG2Seq
13.60
23.37
PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction
-
FasterSTS
13.60
-
FasterSTS: A Faster Spatio-Temporal Synchronous Graph Convolutional Networks for Traffic flow Forecasting
PDFormer
13.58
-
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction
PM-DMNet(P)
13.55
23.35
Pattern-Matching Dynamic Memory Network for Dual-Mode Traffic Prediction
STD-MAE
13.44
22.47
Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting
STWave
13.42
-
When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
-
PM-DMNet(R)
13.40
23.22
Pattern-Matching Dynamic Memory Network for Dual-Mode Traffic Prediction
HTVGNN
13.24
-
A novel hybrid time-varying graph neural network for traffic flow forecasting
-
Hierarchical-Attention-LSTM (HierAttnLSTM)
9.215
22.320
Network Level Spatial Temporal Traffic State Forecasting with Hierarchical-Attention-LSTM (HierAttnLSTM)
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