Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management.
- DOI
- 10.1038/s41598-026-54304-7
- Published
- 2026-07-06
- Container
- Sci Rep
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-54304-7,
title = {Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management.},
author = {Huang B and Niu D and Xu Q and Yang T.},
year = {2026},
journal = {Sci Rep},
doi = {10.1038/s41598-026-54304-7},
url = {https://doi.org/10.1038/s41598-026-54304-7}
}RIS
TY - JOUR TI - Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management. AU - Huang B AU - Niu D AU - Xu Q AU - Yang T. PY - 2026 JO - Sci Rep DO - 10.1038/s41598-026-54304-7 UR - https://doi.org/10.1038/s41598-026-54304-7 ER -
APA
B, H., D, N., Q, X., & T., Y. (2026). Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management.. Sci Rep. https://doi.org/10.1038/s41598-026-54304-7
Source records
- europe-pmc · retrieved 2026-09-26T14:30:47.348Z