Stronger regularization was performed at time points where DL estimations ... compared to the competing methods in terms of RMSE (~50% improvement vs. standard CNN-LSTM; ~24% improvement vs.

The model architecture employs a simplified Long Short-Term Memory (LSTM) network enhanced with an attention mechanism, which enables the model to focus on critical time points in dynamic patient data ...

Watch as Lewis Hamilton has first test in Ferrari F1 car Lewis Hamilton said his first test in a Ferrari Formula 1 car was "awe-inspiring" and "one of the best feelings of my life". The 40-year ...

The proposed architecture consists of two LSTM layers for capturing temporal patterns, a dropout layer for regularization, and a dense layer for yield prediction. The specific hyperparameters adopted ...