Interpretable framework based on stepwise virtual sample generation for accelerating accurate PCDD/Fs prediction and assessing emission control strategies under small-sample conditions | Synapse
March 3, 2026
Interpretable framework based on stepwise virtual sample generation for accelerating accurate PCDD/Fs prediction and assessing emission control strategies under small-sample conditions
Puntos clave
Prediction models enhanced accuracy for PCDD/Fs under small-sample conditions, improving control strategies.
A key improvement was a 30% increase in prediction accuracy using stepwise virtual sample generation.
The framework analyzes emission control strategies through advanced algorithms and predictive modeling.
This method may enable more effective regulation of emissions in emerging areas, requiring further validation.