Case
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Speech Emotion Recognition | CASE Zero-Shot v1 (test) | Accuracy (ACC)59.38 | 12 | |
| Multi-objective Optimization | Case 6 | Mean Hypervolume0.1908 | 6 | |
| Multi-objective Optimization | Case 5 | Mean Hypervolume0.1924 | 6 | |
| Multi-objective Optimization | Case 4 | Mean Hypervolume19.79 | 6 | |
| Multi-objective Optimization | Case 3 | Mean Hypervolume0.1959 | 6 | |
| Multi-objective Optimization | Case 1 | Mean Hypervolume (HV)0.1852 | 6 | |
| Power System Topology Control | CASE118 modified IEEE bus (evaluation) | Average Reward137,420.6 | 4 | |
| Profit Maximization | Case III 2023 | Mean Profit (MWh/Euros)0.733 | 4 | |
| Cost Minimization | Case IV 2023 | Mean Cost0.7026 | 4 | |
| Cost Minimization | Case IV 2021 | Mean Cost0.7307 | 4 | |
| Profit Maximization | Case II 2023 | Mean Profit0.6995 | 4 | |
| Retrodictive Forecasting | Case C | RMSE0.749 | 4 | |
| Retrodictive Forecasting | Case B | RMSE0.066 | 4 | |
| Four-class classification | CASE | F1 Score49.8 | 3 | |
| Valence classification | CASE | F1 Score54 | 3 | |
| Profit Forecasting | Case II 2023 | MAE0.5742 | 3 | |
| Profit Forecasting | Case III 2023 | Mean Absolute Error (MAE)0.5929 | 3 | |
| Profit Forecasting | Case III 2022 | Mean Absolute Error0.4729 | 3 | |
| Airfoil Optimization | Case B3 1.0 (test) | CL, buffet1.11 | 3 | |
| Airfoil Optimization | Case B1 1.0 (test) | CL Buffet1.09 | 3 | |
| Airfoil Optimization | Case A3 1.0 (test) | CL Buffet1.02 | 3 | |
| Airfoil Optimization | Case A1 1.0 (test) | CL Buffet1.17 | 3 | |
| PV cleaning scheduling | Case S5uae (test) | Average Number of Cleanings76 | 2 | |
| PV cleaning scheduling | Case S1uae (test) | Avg Cleanings187 | 2 | |
| PV cleaning scheduling | Case S5exp (test) | Avg Cleanings143 | 2 |
Showing 25 of 33 rows