A neural network model for predicting maximum shear capacity of concrete beams without transverse reinforcement

被引:19
作者
Seleemah, AA [1 ]
机构
[1] Benha High Inst Technol, Dept Civil Engn, Banha, Egypt
关键词
artificial neural networks; shear capacity; transverse reinforcement; beams;
D O I
10.1139/L05-003
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Different relationships have been proposed by codes and researchers for predicting the shear capacity of members without transverse reinforcement. In this paper, the applicability of the artificial neural network (ANN) technique as an analytical alternative to existing methods for predicting this shear capacity is investigated using a critically reviewed and agreed upon database of experimental work that serves as a basis of comparison and (or) assessment of existing and new relationships. Both ANN and eight different codes and researcher's predictions of the shear capacity of the specimens of the database were compared. The ANN predictions are much superior to those of any of the current available relationships.
引用
收藏
页码:644 / 657
页数:14
相关论文
共 21 条
[1]  
ACI Committee, 1999, BUILDING CODE REQUIR
[2]  
[Anonymous], 2001, 10451 DIN
[3]  
[Anonymous], 1995, NZS 3101
[4]  
BSI, 1990, BS54004
[5]  
Carpenter W. C., 1995, AI Expert, V10, P30
[6]   COMMON MISCONCEPTIONS ABOUT NEURAL NETWORKS AS APPROXIMATORS [J].
CARPENTER, WC ;
BARTHELEMY, JF .
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 1994, 8 (03) :345-358
[7]  
*CEB, 1997, B CEB, V237
[8]  
Collins MP, 1999, ACI STRUCT J, V96, P482
[9]  
*ECS, 1992, 199211 DD ENV ECS
[10]   NEURAL NETWORKS IN CIVIL ENGINEERING .1. PRINCIPLES AND UNDERSTANDING [J].
FLOOD, I ;
KARTAM, N .
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 1994, 8 (02) :131-148