Application of Artificial Neural Network (ANN) for predicting the compressive strength of self-compacting concrete containing Fly Ash

Compressive strength is one of the most important characters for quality control of concrete, moreover, this property is highly related to its constituents This paper presents the investigating of Artificial Neural Network (ANN) to predict the compressive strength of self-compacting concrete (SCC) containing fly ash. In this regard, 327 samples of SCC containing fly ash have been used which were collected from the comprehensive literature. The model arranged with seven input parameters including superplasticizer, cement, sand, coarse aggregate, water, fly ash, and age, moreover, the output of this model is the compressive strength of SCC. Through comparisons, the compressive strengths values that were predicted by the ANN model show a good precision with respect to the experimental results. In addition, according to the values of the statistical parameters ANN has acceptable performance

Keywords:

self-compacting concrete , fly ash , compressive strength , Artificial Neural Network ,