Sarıdemir, MustafaBilir, Turhan2024-11-072024-11-0720162515-3048https://hdl.handle.net/11480/110304th International Conference on Sustainable Construction Materials and Technologies, SCMT 2016 -- 7 August 2016 through 11 August 2016 -- Las Vegas -- 137590The gene expression programming that is one of the artificial intelligence techniques, have been commonly used to model some of civil engineering applications. In this study, two models in the gene expression programming for predicting the elastic modulus of concrete containing fly Ash have been developed. First model is proposed for the elastic modulus prediction from compressive strength of concrete containing fly Ash, and second model is proposed for the elastic modulus prediction from amount of fly Ash and compressive strength of concrete containing fly ash. For the aim of building these models, the experimental results for 259 specimens presented with 132 different concrete mixtures were collected from the literature. The training and testing sets of these models are divided without prior planning from the experimental results. These models are also validated with 122 data of experimental results other than the data used in training and testing sets. Moreover, the results obtained from these models are compared with the experimental results and formulas results given by some national building codes. These comparisons revealed that the equations of these models appeared to well concur with the experimental results and found to be very reliable. © 2016 International Committee of the SCMT conferences. All rights reserved.eninfo:eu-repo/semantics/closedAccessCompressive strengthConcrete mixturesElastic moduliFly ashForecastingSustainable developmentArtificial intelligence techniquesCivil engineering applicationsCompressive strength of concreteGene expression programmingNational Building CodeTraining and testingGene expressionConference Object2016-August2-s2.0-85049771517N/A