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조해창 ( Cho Hae-chang ),갈경완 ( Karl Kyoung-wan ),이득행 ( Lee Deuck-hang ),김강수 ( Kim Kang-su ),임주혁 ( Im Ju-hyeik ) 한국구조물진단유지관리공학회 2010 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.14 No.1
In the engineering field, intelligence information processing system have been used to analyse the problem related uncertainty i.e. fussy, neural network, genetic algorithm, genetic programming recently. These method can be applied to predict shear strength of plain concrete, in the structural engineering field, because the previous prediction equations for plain concrete shear strength is based on experiments so they contain uncertainty. In this paper, therefore, Adaptive Neuro-Fuzzy Inference System(ANFIS) which is based on Sugeno Fuzzy model was used to predict shear strength of plain concrete by using 365 previous test results. As test results, ANFIS provided more accurate results than ACI equation for shear strength of plain concrete.
ANFIS를 이용한 강섬유로 보강된 콘크리트 휨부재의 전단강도 평가
조해창(Cho, Hae-Chang),이득행(Lee, Deuck-Hang),황진하(Hwang, Jin-Ha),주현진(Ju, Hyun-Jin),김강수(Kim, Kang-Su),서수연(Seo, Soo-Yeon) 대한건축학회 2013 大韓建築學會論文集 : 構造系 Vol.29 No.6
Steel fiber-reinforced concrete(SFRC) members has improved shear strength compared to typical reinforced concrete members as the steel fibers mixed into concrete improve the tensile performance of concrete. Due to the very complicated shear transfer mechanisms of SFRC members, however, researchers has mostly proposed semi-empirical equations for estimation of shear strength of SFRC members based on test results. In this study, Adaptive Nuero-Fuzzy Inference System(ANFIS) was adopted to evaluate shear strengths of SFRC flexural members. It is known that the ANFIS, which is a knowledge-based model, can provide very accurate analysis results when the reliable and sufficient data are utilized. A total of 172 test data were collected from literature, and used for development of ANFIS shear strength model for SFRC beams, which provided very accurate evaluation of the shear strength of SFRC members.