This research analyzes how machine learning enhances energy consumption optimization in key sectors, indicating improved efficiency and sustainability.
Key Points
Energy consumption optimization has been enhanced using AI, improving predictive accuracy in various sectors.
The study employs several advanced machine learning models, including XGBoost and LSTM, to analyze energy trends.
A data-driven framework integrates time-series analysis and feature engineering to improve model performance.
AI-driven insights may significantly impact cost reduction and environmental sustainability, highlighting policy benefits.