Evaluation of machine learning applications in building life cycle processes for energy efficiency: A systematic review
Yükleniyor...
Tarih
2025-06
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In recent years, machine learning has been increasingly applied to achieve energy efficiency in buildings. This study analyzes the utilization of machine learning across the building life cycle by reviewing literature on building energy efficiency. In this context, a systematic literature search was conducted using the Web of Science (WOS) search engine, and 868 publications were found. The publications were analyzed according to their year, subject scope, and qualification results, and 84 publications were selected. These publications were discussed under five categories: objective function and control variables, programs, simulations, machine learning, and optimization algorithms. The relationships between these categories and each phase of the building life cycle were examined. The findings suggest that machine learning can effectively optimize factors related to energy efficiency and building sustainability throughout the life cycle, and it is anticipated that interdisciplinary studies incorporating machine learning will experience exponential growth in the future.
Açıklama
Anahtar Kelimeler
Building design, Energy efficiency, Life cycle process, Machine learning, Optimization algorithm, Systematic analysis
Kaynak
Energy Reports
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
13
Sayı
Künye
Kaya, G. N., Beyhan, F., İlerisoy, Z. Y., & Cudzik, J. (2025). Evaluation of machine learning applications in building life cycle processes for energy efficiency: A systematic review. Energy Reports, 13, 4900-4916.
