Determination of shear strength of steel fiber RC beams:application of data-intelligence models

作     者：Abeer A.AL-MUSAWI 

作者机构：Projects and Reconstruction DepartmentUniversity of BaghdadBaghdadIraq 

出 版 物：《Frontiers of Structural and Civil Engineering》 (结构与土木工程前沿（英文版）)

年 卷 期：2019年第13卷第3期

页      面：667-673页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 

主　　题：hybrid intelligence model shear strength prediction steel fiber reinforced concrete 

摘      要：Accurate prediction of shear strength of structural engineering components can yield a magnificent information modeling and predesign *** paper aims to determine the shear strength of steel fiber reinforced concrete beams using the application of data-intelligence models namely hybrid artificial neural network integrated with particle swarm *** the considered data-intelligence models,the input matrix attribute is one of the central element in attaining accurate predictive ***,various input attributes are constructed to model the shear strengthas a targeted variable.The modeling is initiated using historical published researches steel fiber reinforced concrete beams *** variables are used as input attribute combination including reinforcement ratio(ρ%),concrete compressive strength(f′c),fiber factor(F1),volume percentage of fiber(Vf),fiber length to diameter ratio(lf/ld)effective depth(d),and shear span-to-strength ratio(a/d),while the shear strength(SS)is the output of the *** best network structure obtained using the network having ten nodes and one hidden *** final results obtained indicated that the hybrid predictive model of ANN-PSO can be used efficiently in the prediction of the shear strength of fiber reinforced concrete *** more representable details,the hybrid model attained the values of root mean square error and correlation coefficient 0.567 and 0.82,respectively.