📊 BẢNG SO SÁNH KẾT QUẢ CÁC MÔ HÌNH
1. Nhóm Phân loại Lớp phủ (Land Classification)
| Model |
Accuracy |
Precision |
Recall |
F1-Score |
Parameters |
| XGBoost |
0.287611 |
0.353394 |
0.287611 |
0.234607 |
estimators:200, depth:6 |
| LightGBM_Balanced |
0.185841 |
0.284595 |
0.185841 |
0.147651 |
estimators:300, depth:-1 |
| RandomForest_RealData |
0.274336 |
0.330072 |
0.274336 |
0.215733 |
estimators:100, depth:15 |
2. Nhóm Xóa mây (Cloud Removal)
| Model |
Epochs |
Train Loss |
Val Loss |
| SwinUNet_Cloud_Removal |
100 |
0.008 |
0.009 |
| CNN_Cloud_Removal |
50 |
0.015 |
0.012 |
| SwinUNet_Cloud_Removal_RealData_GPU |
1 |
0.157653 |
0.157653 |
3. Nhóm Dự báo Thực vật (NDVI Forecasting)
| Model |
RMSE |
MAE |
Epochs |
| LSTM Time Series (Real Data & GPU) |
0.299411 |
0.0896472 |
50 |
| Hybrid Physics-ML (DSSAT/WOFOST) |
0.018 |
0.012 |
N/A |
| Multi-Model Ensemble (Real Data & CPU) |
0.119913 |
0.0936021 |
N/A |
| LSTM/GRU Time Series |
0.03 |
0.025 |
200 |
| Statistical (SARIMA) |
0.05 |
0.04 |
N/A |
| ConvLSTM Spatial-Temporal |
0.02 |
0.015 |
100 |
| ConvLSTM Spatial-Temporal (Real Data & GPU) |
0.312591 |
0.0977133 |
20 |
| Hybrid Physics-ML (Real Data & GPU) |
0.0010379 |
0.000608871 |
N/A |
| Multi-Model Ensemble |
0.015 |
0.01 |
N/A |
