Machine Learning Methods for Estimating Energy Performance of Building Facade Systems
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-97940-9_112
Reference43 articles.
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2. B. Abediniangerabi, S.M. Shahandashti, B. Bell, S.H. Chao, A. Makhmalbaf, in Assembly-Scale and Whole-Building Energy Performance Analysis of Ultra-High-Performance Fiber-Reinforced Concrete (UHP-FRC) Facade Systems. International Interactive Symposium on Ultra-High Performance Concrete, vol. 2(1) (Iowa State University Digital Press, June 2019)
3. B. Abediniangerabi, S.M. Shahandashti, A. Makhmalbaf, A data-driven framework for energy-conscious design of building facade systems. J. Build. Eng. 29, 101172 (2020)
4. S.S. Amiri, M. Mottahedi, S. Asadi, Using multiple regression analysis to develop energy consumption indicators for commercial buildings in the US. Energ. Buildings 109, 209–216 (2015)
5. M. Ashouri, F. Haghighat, B.C. Fung, A. Lazrak, H. Yoshino, Development of building energy saving advisory: a data mining approach. Energ. Buildings 172, 139–151 (2018)
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