Failure criterion of concrete under triaxial stresses using neural networks

Computer-Aided Civil and Infrastructure Engineering

Volumn 17, Issue 1, 2002, Pages 68-73

  Zhao, Zhiye ^a   Ren, Liqun ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; FAILURE (MECHANICAL); MATHEMATICAL MODELS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; STRENGTH OF MATERIALS; STRESSES;

TRIAXIAL STRESSES;

CONCRETES;

CONCRETE;

EID: 0036175508     PISSN: 10939687     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-8667.00254     Document Type: Article

References (16)

1. Strength of concrete under combined stresses
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4. HPC strength prediction using artificial neural network
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6. Concrete strength prediction by means of neural network
7. Fast learning in networks of locally tuned processing units
8. Application of neural networks to the modelling of some constitutive laws
9. Experimental investigation of biaxial and triaxial compressive concrete strength
10. Modeling concrete strength with augment-neural networks
11. Design of high-performance concrete mixture using neural network and nonlinear programming