Prediction of elastic modulus of normal and high strength concrete by artificial neural networks

Demir F.

CONSTRUCTION AND BUILDING MATERIALS, vol.22, no.7, pp.1428-1435, 2008 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 7
  • Publication Date: 2008
  • Doi Number: 10.1016/j.conbuildmat.2007.04.004
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.1428-1435


In the present paper, application of artificial neural networks (ANNs) to predict elastic modulus of both normal and high strength concrete is investigated. The paper aims to show a possible applicability of ANN to predict the elastic modulus of both high and normal strength concrete. An ANN model is built, trained and tested using the available test data gathered from the literature. The ANN model is found to predict elastic modulus of concrete well within the ranges of the input parameters considered. The average value of the experimental elastic modulus to the predicted elastic modulus ratio is found to be 1.00. The elastic modulus results predicted by ANN are also compared to those obtained using empirical results of the buildings codes and various models. These comparisons show that ANNs have strong potential as a feasible tool for predicting elastic modulus of both normal and high strength within the range of input parameters considered. (C) 2007 Elsevier Ltd. All rights reserved.