Upload RecurrentPPO model for WQI prediction

README.md

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----
-license: apache-2.0
----
+
+---
+library_name: stable-baselines3
+tags:
+- stable-baselines3
+- reinforcement-learning
+- RecurrentPPO
+- water-quality-prediction
+---
+
+# RecurrentPPO Model for Water Quality Index Prediction
+
+This model uses RecurrentPPO with an LSTM policy to predict Water Quality Index (WQI) values.
+
+## Model Description
+
+- Model Type: RecurrentPPO
+- Policy: MlpLstmPolicy
+- Training Steps: 10000
+- Average MAPE: 22.08%
+
+## Usage
+
+```python
+from sb3_contrib import RecurrentPPO
+
+# Load the model
+model = RecurrentPPO.load("nctstuti/ds_btl")
+
+# Make predictions
+obs = your_observation  # Shape should match your feature space
+action, _states = model.predict(obs)
+```

metadata.json

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+{"model_type": "RecurrentPPO", "policy_type": "MlpLstmPolicy", "features": ["Place", "pH", "DO", "\u0110\u1ed9 d\u1eabn", "N-NO2", "N-NH4", "P-PO4", "TSS", "COD", "Aeromonas t\u1ed5ng s\u1ed1"], "target": "WQI", "metrics": {"total_steps": 10, "average_mape": 22.08037726170723}}

rppo_wqi_model.zip

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