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Traffic Prediction On Pemsd8

Metriken

12 steps MAE

12 steps RMSE

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			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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