Algorithm 3 Bi-LSTM model training with simulation data

1: Training and validation data samples are loaded. 2: Initialize the parameter of the model, like minibatch size, learning rate, maximum epoch, and Bi-LSTM layer. 3: Actively train the model network 4: Calculate the accuracy error of the model. 5: Compute the corrective parameter using the Adam optimization algorithm and adjust the parameters while looking for the optimal solution. 6: Outcomes: Trained model. 7: Saved the model.