Skip to content
DraconiticResearch
Search Sources API
203,952 studies31 sourcesUpdated 7 min ago
Peer-reviewedCC BY-NC-ND 4.0Scientific Reports

Freeze-thaw model for compressive strength of flowable solidified soil based on machine learning

Versions

Related

  1. Machine learning-based prediction of compressive strength of wastewater-exposed concrete using explainable and optimized models
    Fahid Aslam, Furqan Ahmad
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textCrossref
  2. Interpretable Machine Learning for Compressive Strength Prediction of GGBS–Fly Ash Blended Concrete: Generalization Across Training-Set Compositions and Feature-Attribution Sensitivity
    Materials (Basel, Switzerland)Peer-reviewedCC BYFull textEurope PMC
  3. Bayesian optimization-driven machine learning for compressive strength prediction of hybrid fiber-reinforced recycled aggregate concrete
    Chengjin Li, Runrun Dong, Jawad Tariq +4
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textCrossref
  4. Machine learning prediction of compressive and flexural strength of plastic aggregate concrete using DGAN-augmented data
    Eisa Khan, Muhammad Faisal Javed, Qazi Khurshid Ahmad +4
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textCrossref
  5. Metaheuristic optimized and explainable machine learning for predicting the compressive strength of lightweight foamed concrete
    Ahmed Elsheikh, Muhammad Zeeshan Qureshi, Inamullah Inam +4
    Scientific ReportsPeer-reviewedCC BY 4.0Full textCrossref
BibTeX
@article{wang2026freezethaw,
  title = {{Freeze-thaw model for compressive strength of flowable solidified soil based on machine learning}},
  author = {Baolin Wang and Jinggan Shao and Yunjun Huang and Cong Li and Tingting Han and Bingsen Fan},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-76004-y},
  url = {https://www.nature.com/articles/s41598-026-76004-y},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Freeze-thaw model for compressive strength of flowable solidified soil based on machine learning
AU  - Baolin Wang
AU  - Jinggan Shao
AU  - Yunjun Huang
AU  - Cong Li
AU  - Tingting Han
AU  - Bingsen Fan
PY  - 2026
DA  - 2026/10/15
JO  - Scientific Reports
DO  - 10.1038/s41598-026-76004-y
UR  - https://www.nature.com/articles/s41598-026-76004-y
SN  - 2045-2322
ER  -