Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age

Authors

  • Ilker Ali Ozkan Selçuk Üniversitesi Teknoloji Fakültesi
  • Mustafa ALTIN Selcuk University Higher School of Vocational and Technical Sciences

DOI:

https://doi.org/10.18201/ijisae.263977

Keywords:

Concrete strength, Prediction, Artificial neural networks

Abstract

Compressive strength of concrete is one of the most important elements for an existing building and a new structure to be built. While obtaining the desired compressive strength of concrete with an appropriate mix and curing conditions for a new structure, with non-destructive testing methods for an existing structure or by taking core samples the concrete compressive strength are determined. One of the most important factors that affects the concrete compressive strength is age of concrete. In this study, it is attempted to estimate compressive strength, modelling Artificial Neural Networks (ANN) and using different mixture ratios and compressive strength of concrete samples at different ages. In accordance with obtained data’s in the estimation of concrete compressive strength, ANN could be used safely.

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Published

13.07.2016

How to Cite

[1]
I. A. Ozkan and M. ALTIN, “Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age”, Int J Intell Syst Appl Eng, vol. 4, no. 3, pp. 76–79, Jul. 2016.

Issue

Section

Research Article