After training, validating and testing the models available in the Classification Learner app, the LSTM model, and the NPR tool model, it was seen that the Cubic Support Vector Machine provided the best test accuracy of 99.8% for 100% load. The table below shows the accuracies obtained for each of the models for 12.5% of the load. Model Test Accuracy Train Accuracy ROC (AUC) LSTM 93.04% 92.69% - SDNN 96.9% 96.6% - Quadratic SVM 96.7% 98.5% Class 1 – 0.9995 Class 2 – 0.9999 Class 3 – 0.9993 Class 4 – 0.9994 Class 5 – 0.9994 Cubic SVM 96.6% 98.7% Class 1 – 0.9993 Class 2 – 0.9998 Class 3 – 0.9986 Class 4 – 0.9992 Class 5 – 0.9995