*3.3. Description of the LSTM Model*

LSTM is an advanced RNN used to specify which feature should be memorized or forgotten when the network is being trained. Therefore, given a sufficient history of features and solar radiation, the LSTM can determine the required history for each feature to provide an accurate solar radiation estimation.

In the proposed LSTM/DNN model, we allowed the LSTM to access up to 30 h in the past in order to predict the solar radiation after 48 h. Hyperparameters optimization via grid search was performed on the hyperparameters shown in Table 5.

**Table 5.** Hyper parameters of the LSTM model.


The loss function of LSTM was the mean squared error (MSE) and the model was implemented by Keras.
