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

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.

Authors and Affiliations

Ilker Ali OZKAN*| Selcuk University, Technology Faculty, Computer Engineering, Konya, Turkey, Mustafa ALTIN| Selcuk University Higher School of Vocational and Technical Sciences, Konya, Turkey

Keywords

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  • EP ID EP803
  • DOI 10.18201/ijisae.263977
  • Views 527
  • Downloads 26

How To Cite

Ilker Ali OZKAN*, Mustafa ALTIN (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://europub.co.uk/articles/-A-803