Prediction of Static Modulus and Compressive Strength of Concrete from Dynamic Modulus Associated with Wave Velocity and Resonance Frequency Using Machine Learning Techniques.

Park JY, Sim SH, Yoon YG, Oh TK

Open source

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

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