International Journal of Scientific Engineering and Technology

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Using Neural Network to Predict Compressive Strength of Concrete Containing Additives


Affiliations
1 Shahrekord University, Iran, Islamic Republic of
2 Taft University, United States
 

In this experimental study, polyurethane percentage 1, 1.5, 2.5 and 5 and nanosilica percentage 0.5, 1 and 1.5 were replaced by cement. The purpose of this paper is to examine the impact of predicting results of the addition of nanosilica on compressive strength polymeric concrete with back propagation neural network.

Keywords

Polymeric Concrete, Compressive Strength, Nanosilica, Back Propagation Artificial Neural Network.
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  • Using Neural Network to Predict Compressive Strength of Concrete Containing Additives

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Authors

Ali Heidari
Shahrekord University, Iran, Islamic Republic of
Neda Heidari
Shahrekord University, Iran, Islamic Republic of
Jamal Sheikh
Taft University, United States

Abstract


In this experimental study, polyurethane percentage 1, 1.5, 2.5 and 5 and nanosilica percentage 0.5, 1 and 1.5 were replaced by cement. The purpose of this paper is to examine the impact of predicting results of the addition of nanosilica on compressive strength polymeric concrete with back propagation neural network.

Keywords


Polymeric Concrete, Compressive Strength, Nanosilica, Back Propagation Artificial Neural Network.