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인공신경망을 이용한 강섬유보강콘크리트 보의 전단강도 예측
갈경완(Kal, Kyoung-Wan),이득행(Lee, Deuck-Hang),김강수(Kim, Kang Su) 한국구조물진단유지관리학회 2009 한국구조물진단학회 학술발표회논문집 Vol.2009 No.2
Steel fibers have recently been well recognized for good composite/strengthening materials, which also provide great improvement in shear strength. Consequently, many researchers proposed shear strength prediction models/equations, most of which, however, are based on regression analysis. This is because the shear mechanisms of steel fiber reinforced concrete(SFRC) members are very complicated. Neural network method is useful to predict the complicated shear strength of SFRC members, and is simpler and more accurate than regression analysis method. This paper, therefore, introduces the neural network approach and provides the prediction results of shear strength of 176 SFRC beams obtained from previous studies.
인공신경망을 이용한 강섬 유보강콘크리트 보의 전단강도 예측
갈경완 ( Kal Kyoung-wan ),이득행 ( Lee Deuck-hang ),김강수 ( Kim Kang Su ) 한국구조물진단유지관리공학회 2009 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.13 No.2
Steel fibers have recently been well recognized for good composite/strengthening materials, which also provide great improvement in shear strength. Consequently, many researchers proposed shear strength prediction models/equations. most of which, however, are based on regression analysis. This is because the shear mechanisms of steel fiber reinforced concrete(SFRC) members are very complicated. Neural network method is useful to predict the complicated shear strength of SFRC members, and is simpler and more accurate than regression analysis method. This paper, therefore, introduces the neural network approach and provides the prediction results of shear strength of 176 SFRC beams obtained from previous studies.