TY  - JOUR
TT  - Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age
AU  - Ozkan, Ilker Ali
AU  - Altın, Mustafa
PY  - 2016
DA  - November
DO  - 10.18201/ijisae.263977
JF  - International Journal of Intelligent Systems and Applications in Engineering
PB  - İsmail SARITAŞ
WT  - DergiPark
SN  - 2147-6799
SP  - 76
EP  - 79
VL  - 4
IS  - 3
KW  - Concrete strength
KW  - Prediction
KW  - Artificial neural networks
N2  - Compressive strength of concrete is one of the most important elementsfor an existing building and a new structure to be built. While obtaining thedesired compressive strength of concrete with an appropriate mix and curingconditions for a new structure, with non-destructive testing methods for anexisting structure or by taking core samples the concrete compressive strengthare determined. One of the most important factors that affects the concretecompressive strength is age of concrete. In this study, it is attempted toestimate compressive strength, modelling Artificial Neural Networks (ANN) andusing different mixture ratios and compressive strength of concrete samples atdifferent ages. In accordance with obtained data’s in the estimation ofconcrete compressive strength, ANN could be used safely.
UR  - https://doi.org/10.18201/ijisae.263977
L1  - https://dergipark.org.tr/tr/download/article-file/231852
ER  -