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
- 2022.10
- 수록면
- 313 - 325 (13page)
이용수
초록· 키워드
오류제보하기
Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10<SUP>-3</SUP>, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.
목차
ABSTRACT
1. Introduction
2. Background
3. Methodology
4. Results and Discussion
4. Conclusion
References
참고문헌 (17)
참고문헌 신청
Calabrese, M., Vicinanza, D., & Buccino, M. (2003). 2D wave set up behind low crested and submerged breakwaters. Proceedings of the 13th International Conference ISOPE, Honolulu, Hawaii, USA. https://onepetro.org/ISOPEIOPEC/proceedings/ISOPE03/All-ISOPE03/ISOPE-I-03-321/8542
Daemen, I. F. R. (1991). Wave transmission at low-crested structures [Master thesis, Delft University of Technology]. Delft Hydraulics Report H462.http://resolver.tudelft.nl/uuid:433dfcf3-eb87-4dc9-88dc-8969996a6e3f
Daemrich, K., & Kahle, W. (1985). Protective effect of underwater breakwaters under the influence of irregular sea waves (Report Heft 61). Franzius-Instituts fur Wasserbau und Kusteningenieurswesen.
Formentin, S. M., Zanuttigh, B., & Van der Meer, J. W. (2017). A Neural network tool for predicting wave reflection, overtopping and transmission. Coastal Engineering Journal, 59(1), 1750006. https://doi.org/10.1142/S0578563417500061
Goda, Y., & Ahrens, J. P., (2008). New formulation of wave transmission over and through low-crested structures. Proceedings of the 31st International Conference of Coastal Engineering, Hamburg, Germany, 3530–3541. https://doi.org/10.1142/9789814277426_0292
Formentin, S. M., Zanuttigh, B., & Van der Meer, J. W. (2017). A Neural network tool for predicting wave reflection, overtopping and transmission. Coastal Engineering Journal, 59(1), 1750006. https://doi.org/10.1142/S0578563417500061
Goda, Y., & Ahrens, J. P., (2008). New formulation of wave transmission over and through low-crested structures. Proceedings of the 31st International Conference of Coastal Engineering, Hamburg, Germany, 3530–3541. https://doi.org/10.1142/9789814277426_0292
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