Improved calibration of building models using approximate Bayesian calibration and neural networks-Reference-Cited by-同舟云学术

Improved calibration of building models using approximate Bayesian calibration and neural networks

Published:2022-10-29 Issue:3 Volume:16 Page:291-307
ISSN:1940-1493
Container-title:Journal of Building Performance Simulation
language:en
Short-container-title:Journal of Building Performance Simulation

Author:

Cant Kevin¹,Evins Ralph¹

Affiliation:

1. Energy and Cities Group Department of Civil Engineering, University of Victoria, Victoria, BC, Canada

Funder

Natural Resources Canada

Publisher

Informa UK Limited

Subject

Computer Science Applications,Modeling and Simulation,Building and Construction,Architecture

Link

https://www.tandfonline.com/doi/pdf/10.1080/19401493.2022.2137236

Reference53 articles.

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3. ASHRAE. 2018. Ashrae Standard 211: Standard for Commercial Building Energy Audits. Tech. rep., American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.

4. Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring

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