Applications and Trends of Machine Learning in Building Energy Optimization: A Bibliometric Analysis

• Published in: Buildings (Basel) Vol. 15; no. 7; p. 994
• Main Authors: Liu, Jingyi, Chen, Jianfei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 21.03.2025
• Subjects: Architecture and energy conservation; bibliometric analysis; Bibliometrics; building energy efficiency; Carbon; Construction industry; Data analysis; Data collection; Deep learning; Emissions; Emissions (Pollution); Energy consumption; Energy efficiency; Energy management; energy optimization in buildings; Energy usage; Forecasts and trends; Green buildings; Green design; Learning algorithms; Literature reviews; Machine learning; machine learning (ML); Optimization; Performance prediction; Real time; Scientometrics; Sustainability; Sustainable design; Sustainable development; Trends; Unsupervised learning; Australia; United States; China

With the rapid advancement of machine learning (ML) technologies, their innovative applications in enhancing building energy efficiency are increasingly prominent. Utilizing tools such as VOSviewer and Bibliometrix, this study systematically reviews the body of the related literature, focusing on th...