Algorithm 1 Algorithm for the proposed model

Input: Preprocessed data

Output: Accuracy, loss, precision, recall, F1-score

1:  Standardise (Preprocessed_data)

2:  Shuffle (Preprocessed_data))

3:  Split (Preprocessed_data) based on 70:10:20 (training_data, validating_data, test_data)

4:  Apply CNN layer

5:  Apply LSTM layer

6:  Flatten

7:  Apply Dense

8:  Use Adam optimiser

9:  Use a categorical cross-entropy as loss function

10: for (epoch = 1; epoch < 50; epoch++) do

11:    evaluate loss, validation loss

12:   evaluate accuracy, validation accuracy

13: end for

14: Use testing data to calculate precision, recall, F1-score

15: Calculate loss, accuracy