State-of-the-art on research and applications of machine learning in the building life cycle

Volume: 212, Pages: 109831 - 109831
Published: Apr 1, 2020
Abstract
Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579...
Paper Details
Title
State-of-the-art on research and applications of machine learning in the building life cycle
Published Date
Apr 1, 2020
Volume
212
Pages
109831 - 109831
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.