딥러닝을 통한 콘크리트 강도에 대한 배합 방법 예측에 관한 연구
- Title
- 딥러닝을 통한 콘크리트 강도에 대한 배합 방법 예측에 관한 연구
- Other Titles
- Prediction of concrete mixing proportions using deep learning
- Author
- 이한승
- Keywords
- 딥러닝; 압축강도; 물시멘트비; 배합비율; deep learning; compressive strength; water cement ratio; mix proportion
- Issue Date
- 2021-11
- Publisher
- 한국건축시공학회
- Citation
- 한국건축시공학회 학술발표대회 논문집. Nov 12, 2021 21(2):30
- Abstract
- This study aims to build a deep learning model that can predict the value of concrete mixing properties according to a given
concrete strength value. A model was created for a total of 1,291 concrete data, including 8 characteristics related to
concrete mixing elements and environment, and the compressive strength of concrete. As the deep learning model,
DNN-3L-256N, which showed the best performance on the prior study, was used. The average value for each characteristic
of the data set was used as the initial input value. In results, in the case of ‘curing temperature’, which had a narrow range
of values in the existing data set, showed the lowest error rate with less than 1% error based on MAE. The highest error rate
with an error of 12 to 14% for fly and bfs.
- URI
- https://kiss.kstudy.com/thesis/thesis-view.asp?key=3912138https://repository.hanyang.ac.kr/handle/20.500.11754/169813
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ARCHITECTURE(건축학부) > Articles
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