REFACTOR data service

services/forecasting/app/services/prediction_service.py

@@ -409,7 +409,9 @@ class PredictionService:
                 # Traffic-based features
                 'high_traffic': int(traffic > 150) if traffic > 0 else 0,
                 'low_traffic': int(traffic < 50) if traffic > 0 else 0,
-                'traffic_normalized': float((traffic - 100) / 50) if traffic > 0 else 0.0,
+                # Fix: Use same normalization as training (when std=0, normalized=0.0)
+                # Training uses constant 100.0 values, so std=0 and normalized=0.0
+                'traffic_normalized': 0.0,  # Match training behavior for consistent predictions
                 'traffic_squared': traffic ** 2,
                 'traffic_log': float(np.log1p(traffic)),