Support vector regression based shear strength modelling of deep beams

被引:64
|
作者
Pal, Mahesh [1 ]
Deswal, Surinder [1 ]
机构
[1] NIT Kurukshetra, Dept Civil Engn, Kurukshetra 136119, Haryana, India
关键词
Support vector machines; Deep beam; Shear strength prediction; Strut-and-tie method; Back-propagation neural network; ARTIFICIAL NEURAL-NETWORKS; CONFINED COMPRESSIVE STRENGTH; SCOUR DOWNSTREAM; DESIGN PROCEDURE; PART II; PREDICTION; MACHINES; COLUMNS;
D O I
10.1016/j.compstruc.2011.03.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Support vector regression based modelling approach was used to predict the shear strength of reinforced and prestressed concrete deep beams. To compare its performance, a back-propagation neural network and the three empirical relations was used with reinforced concrete deep beams. For prestressed deep beams, one empirical relation was used. Results suggest an improved performance by the SVR in terms of prediction capabilities in comparison to the empirical relations and back propagation neural network. Parametric studies with SVR suggest the importance of concrete cylinder strength and ratio of shear span to effective depth of beam on strength prediction of deep beams. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1430 / 1439
页数:10
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