A Comprehensive Review of Numerical and Machine Learning Approaches for Predicting Concrete Properties: From Fresh to Long-Term.

Adsul N, Choi Y, Kang ST

DOI: 10.3390/ma18153718
Published: 2025 Aug 7
Container: Materials (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/ma18153718,
  title = {A Comprehensive Review of Numerical and Machine Learning Approaches for Predicting Concrete Properties: From Fresh to Long-Term.},
  author = {Adsul N and Choi Y and Kang ST},
  year = {2025},
  journal = {Materials (Basel, Switzerland)},
  doi = {10.3390/ma18153718},
  url = {https://doi.org/10.3390/ma18153718}
}

RIS

TY  - JOUR
TI  - A Comprehensive Review of Numerical and Machine Learning Approaches for Predicting Concrete Properties: From Fresh to Long-Term.
AU  - Adsul N
AU  - Choi Y
AU  - Kang ST
PY  - 2025
JO  - Materials (Basel, Switzerland)
DO  - 10.3390/ma18153718
UR  - https://doi.org/10.3390/ma18153718
ER  -

APA

N, A., Y, C., & ST, K. (2025). A Comprehensive Review of Numerical and Machine Learning Approaches for Predicting Concrete Properties: From Fresh to Long-Term.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma18153718

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pubmed · retrieved 2026-09-25T16:39:46.110Z