Machine learning-driven building energy optimization: integrating EnsembleXGBoost sensitivity analysis with meta-heuristic algorithms and carbon economics | Synapse
March 3, 2026Open Access
Machine learning-driven building energy optimization: integrating EnsembleXGBoost sensitivity analysis with meta-heuristic algorithms and carbon economics
Key Points
Energy optimization significantly improves with machine learning applications, enhancing carbon economy benefits.
Key evidence includes a marked reduction of up to 25% in energy costs when implementing EnsembleXGBoost algorithms.
Assessment using machine learning and meta-heuristic algorithms was conducted across various building types, demonstrating operational efficiency.
Highlights the need for integrating advanced algorithms for sustainable building management and energy conservation efforts.