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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2018.5
- 수록면
- 13 - 22 (10page)
이용수
초록· 키워드
오류제보하기
The number of researches on the mechanical properties of cemented sand and gravel (CSG) materials and the application of the CSG Dam has been increased. In order to explain the technical scheme of strength prediction model about the artificial neural network, we obtained the sample data by orthogonal test using the PVA (Polyvinyl alcohol) fiber, different amount of cementing materials and age, and established the efficient evaluation and prediction system. Combined with the analysis about the importance of influence factors, the prediction accuracy was above 95%. This provides the scientific theory for the further application of CSG, and will also be the foundation to apply the artificial neural network theory further in water conservancy project for the future.
목차
ABSTRACT
1. Introduction
2. The back propagation neural network
3. Design of experiment
4. Forecasting model
5. Conclusion
References
참고문헌 (19)
참고문헌 신청
[학술지(정기간행물)] - Chai, Q. H. / 2016 / Study on the influence factors of compressive strength of CSG material / Journal of the YELLOW RIVER (China) 38 (7) : 86 ~ 88
[학술지(정기간행물)] - Erdal, H. I. / 2013 / High performance concrete compressive strength forecasting using ensemble models based on discrete wavelet transform / Engineering Applications of Artificial Intelligence : 1246 ~ 1254
[학술지(정기간행물)] - Feng, W. / 2013 / Study on design parameters of mix proportion for cemented sand and gravel (CSG) / Water Resources and Hydropower Engineering (China) 44 (2) : 55 ~ 58
[학술대회논문] - Hanada, H. / 2003 / CSG method using muck excavated from the dam foundation / Proceedings 4th International Symposium on Roller Compacted Concrete Dams : 447 ~ 456
[학술대회논문] - Harkat, M. F. / 2003 / Nonlinear PCA combining principal curves and RBF-Networks for process monitoring / Proceeding of the 42nd IEEE Conference on Decision and Control : 1956 ~ 1961
[학술지(정기간행물)] - Erdal, H. I. / 2013 / High performance concrete compressive strength forecasting using ensemble models based on discrete wavelet transform / Engineering Applications of Artificial Intelligence : 1246 ~ 1254
[학술지(정기간행물)] - Feng, W. / 2013 / Study on design parameters of mix proportion for cemented sand and gravel (CSG) / Water Resources and Hydropower Engineering (China) 44 (2) : 55 ~ 58
[학술대회논문] - Hanada, H. / 2003 / CSG method using muck excavated from the dam foundation / Proceedings 4th International Symposium on Roller Compacted Concrete Dams : 447 ~ 456
[학술대회논문] - Harkat, M. F. / 2003 / Nonlinear PCA combining principal curves and RBF-Networks for process monitoring / Proceeding of the 42nd IEEE Conference on Decision and Control : 1956 ~ 1961
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UCI(KEPA) : I410-ECN-0101-2018-532-002076786