A Systematic Empirical Evaluation of Machine Learning Algorithm on Energy Prediction

The energy crisis has alerted all scientists and researchers in every field. The evident increase in the usage of electronic items causes high electricity consumption. Especially in residential households and high-rise apartments, buildings show high electrical loads. This study is designed to forecast the energy need using AI prediction models and find the most efficient model to predict the future loads of any household considering its surroundings, like weather, air pressure, room temperature and others. This is a comprehensive comparative study that provides a comprehensive comparison between regression models. The finding of the study is that by using the optimum model, we can achieve the best results in predicting electricity load.