Research Article
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Year 2016, Volume: 4 Issue: 3, 76 - 79, 01.11.2016
https://doi.org/10.18201/ijisae.263977

Abstract

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

Year 2016, Volume: 4 Issue: 3, 76 - 79, 01.11.2016
https://doi.org/10.18201/ijisae.263977

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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Details

Subjects Engineering
Journal Section Research Article
Authors

Ilker Ali Ozkan

Mustafa Altın

Publication Date November 1, 2016
Published in Issue Year 2016 Volume: 4 Issue: 3

Cite

APA Ozkan, I. A., & Altın, M. (2016). Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age. International Journal of Intelligent Systems and Applications in Engineering, 4(3), 76-79. https://doi.org/10.18201/ijisae.263977
AMA Ozkan IA, Altın M. Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age. International Journal of Intelligent Systems and Applications in Engineering. November 2016;4(3):76-79. doi:10.18201/ijisae.263977
Chicago Ozkan, Ilker Ali, and Mustafa Altın. “Estimating of Compressive Strength of Concrete With Artificial Neural Network According to Concrete Mixture Ratio and Age”. International Journal of Intelligent Systems and Applications in Engineering 4, no. 3 (November 2016): 76-79. https://doi.org/10.18201/ijisae.263977.
EndNote Ozkan IA, Altın M (November 1, 2016) Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age. International Journal of Intelligent Systems and Applications in Engineering 4 3 76–79.
IEEE I. A. Ozkan and M. Altın, “Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age”, International Journal of Intelligent Systems and Applications in Engineering, vol. 4, no. 3, pp. 76–79, 2016, doi: 10.18201/ijisae.263977.
ISNAD Ozkan, Ilker Ali - Altın, Mustafa. “Estimating of Compressive Strength of Concrete With Artificial Neural Network According to Concrete Mixture Ratio and Age”. International Journal of Intelligent Systems and Applications in Engineering 4/3 (November 2016), 76-79. https://doi.org/10.18201/ijisae.263977.
JAMA Ozkan IA, Altın M. Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age. International Journal of Intelligent Systems and Applications in Engineering. 2016;4:76–79.
MLA Ozkan, Ilker Ali and Mustafa Altın. “Estimating of Compressive Strength of Concrete With Artificial Neural Network According to Concrete Mixture Ratio and Age”. International Journal of Intelligent Systems and Applications in Engineering, vol. 4, no. 3, 2016, pp. 76-79, doi:10.18201/ijisae.263977.
Vancouver Ozkan IA, Altın M. Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age. International Journal of Intelligent Systems and Applications in Engineering. 2016;4(3):76-9.