PS C:\Users\[user]\Desktop\jet-engine-degradation-prediction-master\DANCEST_model\Training> python train_dancest_symbolic.py
2025-05-22 08:32:12.207821: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
WARNING:tensorflow:From C:\Users\Roy.Awill\Desktop\jet-engine-degradation-prediction-master\venv\lib\site-packages\keras\src\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
Starting symbolic model training and optimization (BALANCED MODE)...
This version balances speed and accuracy with appropriate sampling
Loading ground truth data with sampling...
Loading ground truth corrosion data...
Loaded 12500000 ground truth data points
Loaded 500 material data points
Sampled 2500000 records from full dataset
Creating a single estimator for the entire process
Found symbolic model data at: ..\data
Using default parameters for corrosion_rates.json    
Using default parameters for material_properties.json
Using default parameters for environment_params.json 
Using default parameters for region_calibration.json
Loaded symbolic_model_config.json from symbolic_model_config.json
Using default parameters for environment_params.json
Using advanced corrosion mechanisms model
Optimizing symbolic model parameters ...
Using 3 time points for optimization
Reusing existing estimator for optimization
Optimization Progress:   0%|                                                                                                     :00<?, ?itameter optimization ...
Reusing existing estimator for optimization
Optimization Progress:   0%|                                                                                                     :00<?ization Progress:  50%|██████████████████████████████████████████████▌                                              | 1/2 [0Reusing existing estimator for optimization
Optimization Progress:   0%|                                                                                                     :00<?, ?it/s]Running parameter optimization ...
Using advanced corrosion mechanisms model
Optimization Progress:  50%|██████████████████████████████████████████████▌                                              | 1/2 [0t_mae=0.3338]Using advanced corrosion mechanisms model
Optimization Progress: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [2t_mae=0.3338]Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelisms model                     isms model
Using advanced corrosion mechanisms modelUsing advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanUsing advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Using advanced corrosion mechanisms model
Optimization Progress: 100%|██████████████████████████████████████████████████████████████████████████████████████████| 2/2 [4:18est_mae=0.3338]
  uncertainty_reduction_factor: 0.8846
  chromium_protection_threshold: 14.5719
  temperature_threshold: 787.1534
  time_exponent_default: 0.5161
Using advanced corrosion mechanisms model
Performing final evaluation...
Final Evaluation: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [
Final metrics:
  MAE: 0.1682
  RMSE: 0.2059
