Intelligent modeling and prediction of elastic modulus of concrete strength via gene expression programming

Amir Hossein Gandomi, Amir Hossein Alavi, T. O. Ting*, Xin She Yang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

16 Citations (Scopus)


The accurate prediction of the elastic modulus of concrete can be very important in civil engineering applications. We use gene expression programming (GEP) to model and predict the elastic modulus of normal-strength concrete (NSC) and high-strength concrete (HSC). The proposed models can relate the modulus of elasticity of NSC and HSC to their compressive strength, based on reliable experimental databases obtained from the published literature. Our results show that GEP can be an effective method for deriving simplified and precise formulations for the elastic modulus of NSC and HSC. Furthermore, the comparison study in the present work indicates that the GEP predictions are more accurate than other methods.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - 4th International Conference, ICSI 2013, Proceedings
Number of pages8
EditionPART 1
Publication statusPublished - 2013
Event4th International Conference on Advances in Swarm Intelligence, ICSI 2013 - Harbin, China
Duration: 12 Jun 201215 Jun 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7928 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Advances in Swarm Intelligence, ICSI 2013


  • Compressive strength
  • Formulation
  • Gene expression programming
  • Normal and High strength concrete
  • Tangent elastic modulus

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