Neuro-fuzzy model for shear strength of reinforced concrete beams without web reinforcement

被引：13
|
作者：
Cevik, Abdulkadir [1 ]
Ozturk, Sefik [2 ]
机构：
[1] Gaziantep Univ, Dept Civil Engn, Gaziantep, Turkey
[2] State Hydraul Works, Gaziantep, Turkey
来源：
CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS | 2009年 / 26卷 / 03期
关键词：
RC beam; shear strength; neuro-fuzzy; modelling; DEEP BEAMS; CAPACITY; PREDICTION; NETWORKS; STIRRUPS;
D O I：
10.1080/10286600802109927
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
This study investigates the feasibility of a neuro-fuzzy (NF) approach for the modelling of shear strength of reinforced concrete (RC) beams without web reinforcement. The proposed NF model is based on a wide range of experimental data (664 tests) gathered from the literature from 56 separate studies. Various types of membership functions (MFs) such as Gaussian, Gaussian combination, generalised bell-shaped, triangular-shaped and trapezoidal-shaped MFs are evaluated for varying number of MFs to obtain the optimum NF model. The accuracy of the proposed NF model is compared with accuracies of current design codes and existing shear strength equations and found to be more accurate.
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页码：263 / 277
页数：15
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