배합인자를 고려한 딥러닝 알고리즘 기반 탄산화 진행 예측에 관한 기초적 연구
- Title
- 배합인자를 고려한 딥러닝 알고리즘 기반 탄산화 진행 예측에 관한 기초적 연구
- Other Titles
- A Fundamental Study on the Prediction of Carbonation Progress Using Deep Learning Algorithm Considering Mixing Factors
- Author
- 이한승
- Keywords
- 탄산화; 딥러닝; 배합인자; carbonation; deep learning; mixing factor
- Issue Date
- 2019-05
- Publisher
- 한국건축시공학회
- Citation
- 한국건축시공학회 학술발표대회 논문집, v. 19, No. 1, Page. 30-31
- Abstract
- Carbonation of the root concrete reduces the durability of the reinforced concrete, and it is important to check the carbonation resistance of the concrete to ensure the durability of the reinforced concrete structure. In this study, a basic study on the prediction of carbonation progress was conducted by considering the mixing conditions of concrete using deep learning algorithm during the theory of artificial neural network theory. The data used in the experiment used values that converted the carbonation velocity coefficient obtained from the mixing conditions of concrete and the accelerated carbonation experiment into the actual environment. The analysis shows that the error rate of the deep learning model according to the Hidden Layer is the best for the model using five layers, and based on the five Hidden layers, we want to verify the predicted performance of the carbonation speed coefficient of the carbonation test specimen in which the exposure experiment took place in the real environment.
- URI
- http://kiss.kstudy.com/thesis/thesis-view.asp?key=3683058https://repository.hanyang.ac.kr/handle/20.500.11754/121775
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ARCHITECTURE(건축학부) > Articles
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