TBMEnv - An Environment to Assess the Accuracy of Thermal Building Models under Realistic Conditions-Reference-Cited by-同舟云学术

TBMEnv - An Environment to Assess the Accuracy of Thermal Building Models under Realistic Conditions

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
language:
Short-container-title:

Author:

Wölfle David¹^ORCID,Vossberg Samed Rouven¹^ORCID,Schmeck Hartmut²^ORCID

Affiliation:

1. FZI Research Center for Information Technology, Germany

2. Karlsruhe Institute of Technology, Germany and FZI Research Center for Information Technology, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3600100.3625683

Reference19 articles.

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3. Steven L. Brunton and J. Nathan Kutz . 2019. Data Driven Science & Engineering: Machine Learning , Dynamical Systems, and Control . Cambridge University Press , Cambridge New York Port Melbourne New Delhi Singapore. https://doi.org/10.1017/9781108380690 10.1017/9781108380690 Steven L. Brunton and J. Nathan Kutz. 2019. Data Driven Science & Engineering: Machine Learning, Dynamical Systems, and Control. Cambridge University Press, Cambridge New York Port Melbourne New Delhi Singapore. https://doi.org/10.1017/9781108380690

4. HEBO: Pushing The Limits of Sample-Efficient Hyper-parameter Optimisation;Cowen-Rivers I.;Journal of Artificial Intelligence Research 74,2022

5. A family of embedded Runge-Kutta formulae