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Publicité

Chun Fu ORCID

La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Fu, Chun / Kazmi, Hussain / Quintana, Matias / Miller, Clayton (2024): Creating synthetic energy meter data using conditional diffusion and building metadata. Dans: Energy and Buildings, v. 312 (juin 2024).

    https://doi.org/10.1016/j.enbuild.2024.114216

  2. Jin, Xiaoyu / Fu, Chun / Kazmi, Hussain / Balint, Atilla / Canaydin, Ada / Quintana, Matias / Biljecki, Filip / Xiao, Fu / Miller, Clayton (2023): The Building Data Genome Directory – An open, comprehensive data sharing platform for building performance research. Dans: Journal of Physics: Conference Series, v. 2600, n. 3 (1 novembre 2023).

    https://doi.org/10.1088/1742-6596/2600/3/032003

  3. Liguori, Antonio / Quintana, Matias / Fu, Chun / Miller, Clayton / Frisch, Jérôme / van Treeck, Christoph (2024): Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight. Dans: Energy and Buildings, v. 310 (mai 2024).

    https://doi.org/10.1016/j.enbuild.2024.114071

  4. Kazmi, Hussain / Fu, Chun / Miller, Clayton (2023): Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale. Dans: Building and Environment, v. 239 (juillet 2023).

    https://doi.org/10.1016/j.buildenv.2023.110407

  5. Miller, Clayton / Picchetti, Bianca / Fu, Chun / Pantelic, Jovan (2022): Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis. Dans: Science and Technology for the Built Environment, v. 28, n. 5 (avril 2022).

    https://doi.org/10.1080/23744731.2022.2067466

  6. Miller, Clayton / Arjunan, Pandarasamy / Kathirgamanathan, Anjukan / Fu, Chun / Roth, Jonathan / Park, June Young / Balbach, Chris / Gowri, Krishnan / Nagy, Zoltan / Fontanini, Anthony D. / Haberl, Jeff (2020): The ASHRAE Great Energy Predictor III competition: Overview and results. Dans: Science and Technology for the Built Environment, v. 26, n. 10 (octobre 2020).

    https://doi.org/10.1080/23744731.2020.1795514

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