Enhancing the Practicality of Tools to Estimate the Whole Life Embodied Carbon of Building Structures via Machine Learning Models
- DOI
- 10.17863/cam.77473
- Published
- 2021
- Container
- Not recorded
- Publisher
- Frontiers
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.17863/cam.77473,
title = {Enhancing the Practicality of Tools to Estimate the Whole Life Embodied Carbon of Building Structures via Machine Learning Models},
author = {Pomponi, Francesco and Anguita, Maria Luque and Lange, Michal and D’Amico, Bernardino and Hart, Emma},
year = {2021},
doi = {10.17863/cam.77473},
url = {https://doi.org/10.17863/cam.77473}
}RIS
TY - JOUR TI - Enhancing the Practicality of Tools to Estimate the Whole Life Embodied Carbon of Building Structures via Machine Learning Models AU - Pomponi, Francesco AU - Anguita, Maria Luque AU - Lange, Michal AU - D’Amico, Bernardino AU - Hart, Emma PY - 2021 DO - 10.17863/cam.77473 UR - https://doi.org/10.17863/cam.77473 ER -
APA
Francesco, P., Luque, A. M., Michal, L., Bernardino, D., & Emma, H. (2021). Enhancing the Practicality of Tools to Estimate the Whole Life Embodied Carbon of Building Structures via Machine Learning Models. https://doi.org/10.17863/cam.77473
Source records
- datacite · retrieved 2026-09-25T08:01:08.734Z