Prediction of Compressive Strength of Concrete Using Artificial Intelligence

EasyChair Preprint 6272

Abstract

Concrete compressive strength is one of the most important mechanical property because it usually indicates the overall quality of the concrete. Compressive strength of concrete is dependent on many factors such as quality of aggregate, strength of cement, water content, water/cement ratio, binder/aggregate ratio and age of concrete. Compressive strength of concrete is mostly depends on the materials of concrete mix design.  Although the concrete compressive strength can be measured at different ages, codes usually specify standard 28-day testing. When no specific data are available, compressive strength of 28 days is assumed to be 1.5 times the 7-day strength whereas this ratio was shown to vary generally from 1.3 to 1.7 (Neville, 1986). Artificial Neural Network (ANN) is used in this study in order to predict the compressive strength of concrete. MATLAB software is used to predict the compressive strength of concrete using ANN. Result shows that the predicted values are in good correlation with the experimental values.

Keyphrases: Artificial Intelligence, Artificial Neural Network, Neuron, compressive strength

@booklet{EasyChair:6272,
  author    = {S Sushmitha and M Akash and S Jalok and S Ravikumar and V Arjun},
  title     = {Prediction of Compressive Strength of Concrete Using Artificial Intelligence},
  howpublished = {EasyChair Preprint 6272},
  year      = {EasyChair, 2021}}