Prediction of Static Modulus and Compressive Strength of Concrete from Dynamic Modulus Associated with Wave Velocity and Resonance Frequency Using Machine Learning Techniques.
- DOI
- 10.3390/ma13132886
- Published
- 2020 Jun 27
- Container
- Materials (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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BibTeX
@article{allodium:10.3390/ma13132886,
title = {Prediction of Static Modulus and Compressive Strength of Concrete from Dynamic Modulus Associated with Wave Velocity and Resonance Frequency Using Machine Learning Techniques.},
author = {Park JY and Sim SH and Yoon YG and Oh TK},
year = {2020},
journal = {Materials (Basel, Switzerland)},
doi = {10.3390/ma13132886},
url = {https://doi.org/10.3390/ma13132886}
}RIS
TY - JOUR TI - Prediction of Static Modulus and Compressive Strength of Concrete from Dynamic Modulus Associated with Wave Velocity and Resonance Frequency Using Machine Learning Techniques. AU - Park JY AU - Sim SH AU - Yoon YG AU - Oh TK PY - 2020 JO - Materials (Basel, Switzerland) DO - 10.3390/ma13132886 UR - https://doi.org/10.3390/ma13132886 ER -
APA
JY, P., SH, S., YG, Y., & TK, O. (2020). Prediction of Static Modulus and Compressive Strength of Concrete from Dynamic Modulus Associated with Wave Velocity and Resonance Frequency Using Machine Learning Techniques.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma13132886
Source records
- pubmed · retrieved 2026-09-25T17:14:05.632Z
- europe-pmc · retrieved 2026-09-25T17:14:05.650Z