CNN-LSTM Model For Load Forecasting in Iraq 2016

The provided code describes the implementation of a hybrid model that combines Convolutional Neural Networks (CNN) with Long Short-Term Memory networks (LSTM) to analyze and forecast power consumption. Data is processed, split into training and testing sets, and then the model is configured and trained. After training, the model's performance is assessed using metrics like Mean Squared Error (MSE) and others. Finally, the results are visualized to compare the predicted values against the actual ones.