Saridemir, Mustafa2024-11-072024-11-0720171598-81981598-818Xhttps://doi.org/10.12989/cac.2017.19.6.717https://hdl.handle.net/11480/14139In this paper, four formulas are proposed via gene expression programming (GEP)-based models and regression analysis (RA) to predict the flexural strength (f(s)), values of mortars containing different mineral admixtures that are ground granulated blast-furnace slag (GGBFS), silica fume (SF) and fly ash (FA) at different ages. Three formulas obtained from the GEP-I, GEP-II and GEP-III models are constituted to predict the f(s) values from the age of specimen, water-binder ratio and compressive strength. Besides, one formula obtained from the RA is constituted to predict the f(s) values from the compressive strength. To achieve these formulas in the GEP and RA models, 972 data of the experimental studies presented with mortar mixtures were gathered from the literatures. 734 data of the experimental studies are divided without pre-planned for these formulas achieved from the training and testing sets of GEP and RA models. Beside, these formulas are validated with 238 data of experimental studies un-employed in training and testing sets. The f(s) results obtained from the training, testing and validation sets of these formulas are compared with the results obtained from the experimental studies and the formulas given in the literature for concrete. These comparisons show that the results of the formulas obtained from the GEP and RA models appear to well compatible with the experimental results and find to be very credible according to the results of other formulas.eninfo:eu-repo/semantics/closedAccessmineral admixturesflexural-compressive strengthsgene expression programmingArticle19671772410.12989/cac.2017.19.6.7172-s2.0-85021068336Q1WOS:000404351400013Q2