Your download is now in progress and you may close this window

Did you know that with a free Taylor & Francis Online account you can gain access to the following benefits?

Choose new content alerts to be informed about new research of interest to you
Easy remote access to your institution's subscriptions on any device, from any location
Save your searches and schedule alerts to send you new results
Export your search results into a .csv file to support your research

Have an account?
Login now Don't have an account?
Register for free

Login or register to access this feature

Have an account?
Login now Don't have an account?
Register for free

Choose new content alerts to be informed about new research of interest to you
Easy remote access to your institution's subscriptions on any device, from any location
Save your searches and schedule alerts to send you new results
Export your search results into a .csv file to support your research

Search in:

Advanced search

Journal of Building Performance Simulation Latest Articles

Submit an article Journal homepage

Views

CrossRef citations to date

Altmetric

Review Article

A neural network-based surrogate model to predict building features from heating and cooling load signatures

Shane Ferreiraa Department of Civil and Environmental Engineering, Carleton University, Ottawa, CanadaCorrespondence[email protected]
View further author information

Burak Gunaya Department of Civil and Environmental Engineering, Carleton University, Ottawa, CanadaView further author information

Adam Willsb Construction Research Centre, National Research Council Canada, Ottawa, CanadaView further author information

Farzeen Rizvib Construction Research Centre, National Research Council Canada, Ottawa, CanadaView further author information

Received 25 Sep 2023, Accepted 26 Jun 2024, Published online: 17 Jul 2024

Cite this article
https://doi.org/10.1080/19401493.2024.2375304
CrossMark

Full Article
Figures & data
References
Supplemental
Citations
Metrics
Reprints & Permissions

Supplemental material

Neural Network Based Surrogate Model to Estimate Building Features from Heating and Cooling Load Signatures.docx

Download MS Word (79.1 MB)

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Share icon
Back to Top

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.

People also read
Recommended articles
Cited by

To cite this article:

Reference style: APA Chicago Harvard

Citation copied to clipboard

Reference styles above use APA (6th edition), Chicago (16th edition) & Harvard (10th edition)

Download citation

Download a citation file in RIS format that can be imported by citation management software including EndNote, ProCite, RefWorks and Reference Manager.

Choose format: RIS BibTex RefWorks Direct Export

Choose options: Citation Citation & abstract Citation & references