Journal of Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회논문집)

Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회)
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Calculating Expected Damage of Breakwater Using Artificial Neural Network for Wave Height Calculation

파고계산 인공신경망을 이용한 방파제 기대피해도 산정

  • Kim, Dong-Hyawn (Department of Coastal Construction Engineering, Kunsan National University) ;
  • Kim, Young-Jin (Department of Ocean Industrial Engineering, Kunsan National University) ;
  • Hur, Dong-Soo (Department of Ocean Civil Engineering (Institute of Marine Industry), Gyeongsang National University) ;
  • Jeon, Ho-Sung (Department of Ocean Civil Engineering (Institute of Marine Industry), Gyeongsang National University) ;
  • Lee, Chang-Hoon (Department of Civil & Environmental Engineering, Sejong University)
  • 김동현 (군산대학교 해양건설공학과) ;
  • 김영진 (군산대학교 해양산업공학과) ;
  • 허동수 (경상대학교 해양토목공학과) ;
  • 전호성 (경상대학교 해양토목공학과) ;
  • 이창훈 (세종대학교 토목환경공학과)
  • Received : 2010.03.17
  • Accepted : 2010.04.25
  • Published : 2010.04.30
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Abstract

An approach to calculating expected damage of breakwater assisted by artificial neural network was developed. Wave height in front of a breakwater was predicted by a trained artificial neural network with inputs of wave height in deep ocean and tidal level. Prediction results by the neural network can be comparable to that by professional numerical model for wave transformation. Using the wave prediction neural network, it was very easy and fast to obtain a number of significant waves at breakwater and finally analysis time for expected damage can be shortened. In addition, the effect of considering tidal level in the calculation of expected damage was revealed by comparing the expected damages with and without tidal variation. Therefore, it was pointed out that tidal variation should be considered to improve prediction accuracy.

천해파 예측 인공신경망을 이용한 방파제 기대피해도 산정방법을 개발하였다. 극치분포를 따르는 심해파고를 이용하여 방파제 위치에서의 유의파고를 얻기 위해 인공신경망을 이용하였다. 조위와 심해파를 입력받은 인공신경망이 천해유의파를 예측할 수 있도록 학습시켰으며 파랑변형 해석에 사용되는 수치모델(SWAN)의 예측결과와 대등한 성능을 보였다. 천해파 예측 인공신경망을 이용함으로써 다수의 천해파를 매우 손쉽고 빠르게 얻을 수 있었으며 결과적으로 기대피해도 해석에 사용되는 시간을 단축할 수 있었다. 또한, 파고예측 시 방파제 위치에서의 조위 변동성에 따른 기대피해도를 상호비교함으로써 조위변동성을 고려하지 않을 경우 기대피해도를 과다 또는 과소 평가할 수 있음을 확인하였다.

Keywords

References

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