Data-driven estimation of building energy consumption with multi-source heterogeneous data

• Main Authors: Pan, Yue, Zhang, Limao
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Civil engineering; Data Mining; Feature Importance
• Online Access: https://hdl.handle.net/10356/155499
• Institution: Nanyang Technological University

For better energy evaluation and management, a categorical boosting (CatBoost)-based predictive method is presented to accurately estimate building energy consumption by learning large volumes of multi-source heterogeneous data collected from buildings. To be specific, the newly-developed CatBoost m...