Civil Engineering and Architecture Vol. 1(3), pp. 96 - 102
DOI: 10.13189/cea.2013.010306
Reprint (PDF) (296Kb)

Using Artificial Neural Network to Predict the Compressive Strength of Concrete containing Nano-silica

Sakshi Gupta^*
Department of Civil Engineering, Dronacharya College of Engineering, Gurgaon, Haryana, India

ABSTRACT

This paper presents application of artificial neural network to develop model for predicting 28 days compressive strength of concrete with partial replacement of cement with nano-silica for which the data has been taken from various literatures. The use of nano-particle materials in concrete can add many benefits that are directly related to the durability of various cementitious materials, besides the fact that it is possible to reduce the quantities of cement in the composite. The performance of the model can be judged by the correlation coefficient, mean absolute error and root mean square error have been adopted as the comparative measures against the experimental results obtained from the literature.

KEYWORDS
Artificial Neural Network, Nano-Silica, Concrete, Compressive Strength, Partial Replacement

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Sakshi Gupta , "Using Artificial Neural Network to Predict the Compressive Strength of Concrete containing Nano-silica," Civil Engineering and Architecture, Vol. 1, No. 3, pp. 96 - 102, 2013. DOI: 10.13189/cea.2013.010306.

(b). APA Format:
Sakshi Gupta (2013). Using Artificial Neural Network to Predict the Compressive Strength of Concrete containing Nano-silica. Civil Engineering and Architecture, 1(3), 96 - 102. DOI: 10.13189/cea.2013.010306.