Comparative Analysis of ARIMA, LSTM, Prophet, and XGBoost for Energy Consumption Forecasting

This document addresses the challenges in energy forecasting, detailing datasets, preprocessing methods, and experimental setups. It explores methodology with a focus on ARIMA comparisons, presents quantitative results, including accuracy metrics (MAE, RMSE, MAPE), and visual comparisons of forecasts versus actual data. Key insights, model trade-offs, and future research directions are discussed.