Neural networks for predicting compressive strength of structural light weight concrete
MM Alshihri, AM Azmy, MS El-Bisy - Construction and Building Materials, 2009 - Elsevier
Neural networks procedures provide a reliant analysis in several science and technology
fields. Neural network is often applied to develop statistical models for intrinsically non-linear …
fields. Neural network is often applied to develop statistical models for intrinsically non-linear …
Concrete compressive strength using artificial neural networks
PG Asteris, VG Mokos - Neural Computing and Applications, 2020 - Springer
The non-destructive testing of concrete structures with methods such as ultrasonic pulse
velocity and Schmidt rebound hammer test is of utmost technical importance. Non …
velocity and Schmidt rebound hammer test is of utmost technical importance. Non …
[PDF][PDF] Application of artificial neural networks to predict compressive strength of high strength concrete
A method to predict 28-day compressive strength of high strength concrete (HSC) by using
MFNNs is proposed in this paper. The artificial neural networks (ANN) model is constructed …
MFNNs is proposed in this paper. The artificial neural networks (ANN) model is constructed …
Prediction of compressive strength of concrete by neural networks
HG Ni, JZ Wang - Cement and Concrete Research, 2000 - Elsevier
In this paper, a method to predict 28-day compressive strength of concrete by using multi-
layer feed-forward neural networks (MFNNs) was proposed based on the inadequacy of …
layer feed-forward neural networks (MFNNs) was proposed based on the inadequacy of …
[PDF][PDF] The use of neural networks in concrete compressive strength estimation
M Bilgehan, P Turgut - Computers and Concrete, 2010 - academia.edu
Testing of ultrasonic pulse velocity (UPV) is one of the most popular and actual non-
destructive techniques used in the estimation of the concrete properties in structures. In this …
destructive techniques used in the estimation of the concrete properties in structures. In this …
Artificial neural networks for the prediction of compressive strength of concrete
In the paper, an artificial neural network (ANN) model is proposed to predict the compressive
strength of concrete. For developing the ANN model the data bank on concrete compressive …
strength of concrete. For developing the ANN model the data bank on concrete compressive …
Prediction of elastic modulus of normal and high strength concrete by artificial neural networks
F Demir - Construction and building Materials, 2008 - Elsevier
In the present paper, application of artificial neural networks (ANNs) to predict elastic
modulus of both normal and high strength concrete is investigated. The paper aims to show …
modulus of both normal and high strength concrete is investigated. The paper aims to show …
[PDF][PDF] Compressive strength prediction of limestone filler concrete using artificial neural networks
The use of optimum content of supplementary cementing materials (SCMs) such as
limestone filler (LF) to blend with Portland cement has been resulted in many environmental …
limestone filler (LF) to blend with Portland cement has been resulted in many environmental …
Application of neural networks for estimation of concrete strength
The uniaxial compressive strength of concrete is the most widely used criterion in producing
concrete. Although testing of the uniaxial compressive strength of concrete specimens is …
concrete. Although testing of the uniaxial compressive strength of concrete specimens is …
Prediction model for compressive strength of basic concrete mixture using artificial neural networks
In the present paper, we propose a prediction model for concrete compressive strength
using artificial neural networks. In experimental part of the research, 75 concrete samples …
using artificial neural networks. In experimental part of the research, 75 concrete samples …