한국지반공학회논문집 (Journal of the Korean Geotechnical Society)

  • 제16권2호
  • /
  • Pages.71-77
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  • 2000
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  • 1229-2427(pISSN)
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  • 2288-646X(eISSN)
한국지반공학회 (Korean Geotechnical Society)
권호 표지

모듈형 인공신경망을 이용한 연직배수공법에서의 압밀침하량 예측

Prediction of Consolidation Settlements at Vertical Drain Using Modular Artificial Neural Networks

  • 민덕기 (울산대학교 공과대학 토목공학과) ;
  • 황광모 (울산대학교 공과대학 토목공학과 박사 과정) ;
  • 전형원 (울산대학교 공과대학 토목공학과 석사 과정)
  • 발행 : 2000.04.01
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초록

In this paper, consolidation settlements with time at vertical drain sites were predicted by artificial neural networks. Laboratory test results and field measurements of two vertical drain sites were used for training and testing neural networks. Predicted consolidation settlements by trained artificial neural networks were compared with measured settlements by field instrumentation. To improve the prediction accuracy, modular artificial neural networks were studied. From the results of applying artificial neural networks to the same situation, it was shown that modular artificial neural network model was more accurate for the prediction of the consolidation settlements than the general model.

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참고문헌

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