Influence of building parameters on energy efficiency levels: a Bayesian network study-Reference-Cited by-同舟云学术

Influence of building parameters on energy efficiency levels: a Bayesian network study

Published:2022-08-17 Issue:6 Volume:16 Page:780-805
ISSN:1751-2549
Container-title:Advances in Building Energy Research
language:en
Short-container-title:Advances in Building Energy Research

Author:

Senarathne Lakmini Rangana¹,Nanda Gaurav¹,Sundararajan Raji¹

Affiliation:

1. School of Engineering Technology, Purdue University, West Lafayette, IN, USA

Publisher

Informa UK Limited

Subject

Building and Construction

Link

https://www.tandfonline.com/doi/pdf/10.1080/17512549.2022.2108142

Reference46 articles.

1. Estimating energy savings of ultra-high-performance fibre-reinforced concrete facade panels at the early design stage of buildings using gradient boosting machines

2. Aldawoud, A. (2017). “The performance-based design: An innovative approach in design practices and architectural education. 8th International Forum on Engineering Education (IFEE2017) Advances in Engineering Education, no. April.

3. Impact of glazing to wall ratio in various climatic regions: A case study

4. Application of passive measures for energy conservation in buildings – a review

5. Initial approximation of the implications for architecture due to climate change

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