DBS-Adam, which scales learning rates by batch difficulty from EMA gradient norms and loss, reaches 95.22% accuracy on Bi-LSTM accident severity prediction and shows statistically significant precision gains over AMSGrad, AdamW and AdaBound.
Real-Time Crash Risk Prediction using Long Short-Term Memory Recurrent Neural Network,
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Novel Dynamic Batch-Sensitive Adam Optimiser for Vehicular Accident Injury Severity Prediction
DBS-Adam, which scales learning rates by batch difficulty from EMA gradient norms and loss, reaches 95.22% accuracy on Bi-LSTM accident severity prediction and shows statistically significant precision gains over AMSGrad, AdamW and AdaBound.