지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2023.10
- 수록면
- 225 - 234 (10page)
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초록· 키워드
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This study aims to predict how reinforced concrete beams perform under shear stress using Artificial Neural Networks (ANN) and numerical crack data. The shear crack data from reinforced concrete beam specimens through finite element analysis were obtained. Afterward, K-clustering to create an input dataset for the ANN analysis was used. The training and testing of a multi-layer perceptron regression model involved the use of samples that had been analyzed using the Finite Element Method (FEM). The evaluation of the ANN model’s performance considered the Mean Absolute Error (MAE), Adjusted R squared, Coefficient of Correlation, and Coefficient of Variation (CV).
목차
Abstract
1. 서론
2. 해석연구
3. 기계학습 연구
4. 연구 결과
5. 결론
REFERENCES
참고문헌 (25)
참고문헌 신청
MoLIT. (2023). Current status of building. (In Korean) http://www.molit.go.kr/USR/NEWS/m_71/dtl.jsp?lcmspage=1&id=95087983
Cladera, A., & Marí, A. R. (2004). Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II: beams with stirrups. Engineering Structures, 26(7), 927-936.
Adhikary, B. B., & Mutsuyoshi, H. (2006). Prediction of shear strength of steel fiber RC beams using neural networks. Construction and Building Materials, 20(9), 801-811.
Tanarslan, H. M., Secer, M., & Kumanlioglu, A. (2012). An approach for estimating the capacity of RC beams strengthened in shear with FRP reinforcements using artificial neural networks. Construction and Building Materials, 30, 556-568.
Oreta, A. W. C. (2019). Bond strength prediction model of corroded reinforcement in concrete using neural network. GEOMATE Journal, 16(54), 55-61.
Cladera, A., & Marí, A. R. (2004). Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II: beams with stirrups. Engineering Structures, 26(7), 927-936.
Adhikary, B. B., & Mutsuyoshi, H. (2006). Prediction of shear strength of steel fiber RC beams using neural networks. Construction and Building Materials, 20(9), 801-811.
Tanarslan, H. M., Secer, M., & Kumanlioglu, A. (2012). An approach for estimating the capacity of RC beams strengthened in shear with FRP reinforcements using artificial neural networks. Construction and Building Materials, 30, 556-568.
Oreta, A. W. C. (2019). Bond strength prediction model of corroded reinforcement in concrete using neural network. GEOMATE Journal, 16(54), 55-61.
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