Ocean and Polar Research

한국해양과학기술원 (Korea Institute of Ocean Science & Technology)
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신경망을 활용한 사석식 방파제의 파괴확률예측

Prediction of Failure Probability of Breakwater using Neural Network

  • 김동현 (한국해양연구원 연안.항만공학연구본부) ;
  • 박우선 (한국해양연구원 연안.항만공학연구본부) ;
  • 한상훈 (한국해양연구원 연안.항만공학연구본부)
  • Kim, Dong-Hyawn (Coastal and Harbor Engineering Research Division, KORDI) ;
  • Park, Woo-Sun (Coastal and Harbor Engineering Research Division, KORDI) ;
  • Han, Sang-Hun (Coastal and Harbor Engineering Research Division, KORDI)
  • 발행 : 2003.09.30
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초록

A new approach to reliability analysis of rubble mound breakwater using neural network is proposed. At first, a neural network model which can estimate the stability number of any breakwaters for some design conditions is trained. Then, the neural network model is integrated with Monte Carlo simulation technique in order to calculate probability of failure for the breakwater. The proposed technique is compared with conventional approach using empirical formula.

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참고문헌

  1. 김동현, 박우선, 한상훈. 2001. 신경망을 이용한 방파제 피복재의 안정성 예측. 2001년도 대학토목학회 학술발표회논문집, CD ROM.
  2. 김동현, 박우선, 한상훈. 2002. 방파제 피복재의 안정해석을 위한 신경망모델의 개발. 대한토목학회논문집, 22(4-B), 565-572.
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  4. Mase, H., M. Sakamoto, and T. Sakai. 1995. Neural network for stability analysis of rubble-mound breakwater. J. Wtrwy. Port. Coast. and Oc. Engrg., ASCE, 121(6), 294-299. https://doi.org/10.1061/(ASCE)0733-950X(1995)121:6(294)
  5. van der Meer, J.W. 1988. Rock slopes and gravel beaches under wave attack, PhD Thesis, Delft Univ. of Technol., Delft, The Netherlands.