Mobile QR Code QR CODE

Journal of the Korea Concrete Institute

ISO Journal TitleJ Korea Concr Inst.
  • SCOPUS
  • KCI Accredited Journal

Journal Search

  1. Home
  2. All Issues
  3. 2025-08 (Vol.37 No.4)
  4. 10.4334/JKCI.2025.37.4.481
Export citation EndNote
XML PDF INFO REF

References

1 
Gu, J. M. (2024) Prediction of Concrete Compression Strength Using Machine Learning. Master’s thesis, Gyeongsang National University.URL
2 
Jang, H. J. (2023) Concrete Quality Control According to Unit Water Content Measurement and Present Improvement Plan. Master’s thesis, Kyungpook National University.URL
3 
KATS (2022) Cement–Test methods–Determination of Strength (KS L ISO679 4009). Seoul, Korea: Korea Agency for Technology and Standards (KATS), Korea Standard Association (KSA). 1-32. (In Korean)URL
4 
KCI (2022) Ready-mixed Concrete Unit Quantity Rapid Measurement Method (KCI-RM101). Seoul Korea; Korea Concrete Institute (KCI). 2-8. (In Korean)URL
5 
KCI (2024) General Concrete (KCS 14 20 10). Seoul, Korea, Korea Concrete Institute (KCI), Ministry of Land, Infrastructure and Transport (MOLIT). (In Korean)URL
6 
Lee, S. J. (2019) A Fundamental Study on Development of the Predictive System for Compressive Strength of Concrete Based on Deep Learning Algorithms. Master’s thesis, Hanyang University.URL
7 
Park, M. Y. (2022) Evaluation of the Field Applicability and Suggestion of Test Method for Unit Water Content of Concrete. Ph.D. thesis, Cheongju University.URL
8 
Rita Angelou (2025) Top 10 Common ML Algorithms Every Data Scientist Should Know: Part 2. Available at: https://python.plainenglish.io/top-10-common-ml-algorithms-every-data-scientist-should-know-part-2-fce7e588e8e1 (Accessed: 19 June 2025).URL