Currently, artificial neural networks are being widely used in various fields of science and engineering. Neural networks have the ability to learn through experience and existing examples, and then generate solutions and answers to new problems, involving even the effects of non-linearity in their variables. The aim of this study is to use a feed-forward neural network with back-propagation technique, to predict the values of compressive strength and modulus of elasticity, at 28 days, of different concrete mixtures prepared and tested in the laboratory. It demonstrates the ability of the neural networks to quantify the strength and the elastic modulus of concrete specimens prepared using different mix proportions
A method to predict 28-day compressive strength of high strength concrete (HSC) by using MFNNs is pr...
Modulus of elasticity (MOE) is one of the main factors that affect the deformation characteristics a...
Concrete is the most generally used structural material for construction these days. Traditionally, ...
Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although tes...
This paper presents the optimization of concrete mixtures composition related to a physical property...
Artificial neural networks (ANNs) are the result of academic investigations that use mathematical fo...
Karaci, Abdulkadir/0000-0002-2430-1372; Demir, Ilhami/0000-0002-8230-4053WOS: 000313062100015The pre...
Aggregates mineralogical, and petrographic properties directly affect the mechanical properties of t...
This paper presents machine learning (ML) models for high fidelity prediction of compressive strengt...
A new formulation to estimate the elastic modulus of concrete containing recycled coarse aggregate i...
Structures are a combination of various load carrying members which transfer the loads to the founda...
The uniaxial compressive strength of concrete is the most widely used criterion in producing concret...
WOS: 000264576600005Neural networks have recently been widely used to model some of the human activi...
Cases of collapsed buildings and structures are prevalent in Nigeria. In most of these cases the cau...
Cases of collapsed buildings and structures are prevalent in Nigeria. In most of these cases the cau...
A method to predict 28-day compressive strength of high strength concrete (HSC) by using MFNNs is pr...
Modulus of elasticity (MOE) is one of the main factors that affect the deformation characteristics a...
Concrete is the most generally used structural material for construction these days. Traditionally, ...
Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although tes...
This paper presents the optimization of concrete mixtures composition related to a physical property...
Artificial neural networks (ANNs) are the result of academic investigations that use mathematical fo...
Karaci, Abdulkadir/0000-0002-2430-1372; Demir, Ilhami/0000-0002-8230-4053WOS: 000313062100015The pre...
Aggregates mineralogical, and petrographic properties directly affect the mechanical properties of t...
This paper presents machine learning (ML) models for high fidelity prediction of compressive strengt...
A new formulation to estimate the elastic modulus of concrete containing recycled coarse aggregate i...
Structures are a combination of various load carrying members which transfer the loads to the founda...
The uniaxial compressive strength of concrete is the most widely used criterion in producing concret...
WOS: 000264576600005Neural networks have recently been widely used to model some of the human activi...
Cases of collapsed buildings and structures are prevalent in Nigeria. In most of these cases the cau...
Cases of collapsed buildings and structures are prevalent in Nigeria. In most of these cases the cau...
A method to predict 28-day compressive strength of high strength concrete (HSC) by using MFNNs is pr...
Modulus of elasticity (MOE) is one of the main factors that affect the deformation characteristics a...
Concrete is the most generally used structural material for construction these days. Traditionally, ...