Traffic Prediction On Nycbike1
Metriken
MAE @ in
MAE @ out
MAPE (%) @ in
MAPE (%) @ out
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | MAE @ in | MAE @ out | MAPE (%) @ in | MAPE (%) @ out | Paper Title | Repository |
|---|---|---|---|---|---|---|
| AGCRN | 5.17 | 5.47 | 25.59 | 26.63 | Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting | |
| STFGNN | 6.53 | 6.79 | 32.14 | 32.88 | Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting | |
| ST-SSL | 4.94 | 5.26 | 23.69 | 24.6 | Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction | |
| STSGCN | 5.81 | 6.10 | 26.51 | 27.56 | Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting |
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