KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Prediction of Local Scour Around Bridge Piers Using GEP Model

GEP 모형을 이용한 교각주위 국부세굴 예측

  • 김태준 (연세대학교 대학원 토목환경공학과) ;
  • 최병웅 (연세대학교 토목환경공학과) ;
  • 최성욱 (연세대학교 공과대학 토목환경공학과)
  • Received : 2014.06.03
  • Accepted : 2014.09.18
  • Published : 2014.12.01
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Abstract

Artificial Intelligence-based techniques have been applied to problems where mathematical relations can not be presented due to complicatedness of the physical process. A representative example in hydraulics is the local scour around bridge piers. This study presents a GEP model for predicting the local scour around bridge piers. The model is trained by 64 laboratory data to build the regression equation, and the constructed model is verified against 33 laboratory data. Comparisons between the models with dimensional and normalized variables reveals that the GEP model with dimensional variables predicts better. The proposed model is now applied to two field datasets. It is found that the MAPE of the scour depths predicted by the GEP model increases compared with the predictions of local scours in laboratory scale. In addition, the model performance increases significantly when the model is trained by the field dataset rather than the laboratory dataset. The findings suggest that apart from the ANN model, GEP model is a sound and reliable model for predicting local scour depth.

물리현상의 난해성으로 인해 수학적인 관계식이 제시되기 어려운 경우 인공지능 기술에 근거한 다양한 기법이 적용되어 왔다. 수리학 분야의 대표적인 예로 교각주위 국부세굴 문제를 들 수 있다. 본 연구에서는 유전자 알고리즘의 진화된 방법인 GEP 기법을 이용하여 교각주위 국부세굴을 예측하는 방법을 제시하였다. 64개의 실험 자료를 이용하여 GEP 모형을 학습시켜 회귀식을 구축하였으며, 33개의 실험 자료를 이용하여 구축된 모형의 검증을 실시하였다. 평형세굴심 예측을 위하여 차원을 갖는 일반 변수와 표준화된 변수로 GEP 모형을 구축하여 예측 결과를 비교하였는데, 차원을 갖는 변수에 의한 GEP 모형이 세굴심을 더 잘 예측하는 것으로 나타났다. 구축된 GEP 모형을 두 가지 현장 실측자료에 적용하였다. 적용 결과, 실험 자료에 적용한 경우에 비해 예측의 정확도가 낮아지는 것을 확인하였다. 또한, 현장 실측자료를 이용하여 학습시킨 경우 실험 자료를 이용하는 경우 보다 예측 능력이 많이 향상되는 것으로 나타났다. GEP 모형의 적용성을 위해 ANN 모형과의 비교를 수행하였으며, 본 연구에서 사용된 GEP 모형이 교각주위 국부세굴 예측에 대하여 실내 및 현장 모두 ANN 모형보다 우수한 것으로 나타났다.

Keywords

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