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신경망 기법을 이용한 강섬유 혼입 콘크리트의 전단강도 추정 모형 개발

Development of Model of Shear Strength Estimative for Steel Fiber Reinforced Concrete Using Neural Network

  • 곽계환 (원광대학교 토목환경, 도시공학부) ;
  • 황해성 (원광대학교 대학원 토목환경공학과) ;
  • 김우종 (원광대학교 대학원 토목환경공학과) ;
  • 장화섭 (원광대학교 대학원 토목환경공학과) ;
  • 강신묵 (원광대학교 대학원 토목환경공학과)
  • 발행 : 2007.03.31

초록

This study, the present study wishes to develop a model that estimates shear strength characteristics of steel fiber reinforced concrete using artifical neural network models. Neural network models, developed as mathematical models, are being widely used not only in its original purpose of pattern recognition, but also in application fields by the function's nonlinear loaming and interpolar ability Neural network has a repetitive rotation algorithm that can cyclically and repeatedly estimate system conditions and parameter ideal values, and it can be used in the modeling of the nonlinear system by nonlinear characteristic functions that construct the system.

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참고문헌

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