Altın, MustafaSarıtaş, İsmailÇöğürcü, Mustafa TolgaTaşdemir, ŞakirKamanlı, MehmetKaltakcı, M. Yaşar2020-03-262020-03-2620089.78955E+12https://dx.doi.org/10.1145/1500879.1500924https://hdl.handle.net/20.500.12395/228579th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, CompSysTech'08 -- 12 June 2008 through 13 June 2008 -- Gabrovo -- 76845In this study, in order to determine the resistance characteristics of self-compacting concrete (SCC) samples, experiments were done in the Konya Cement Factory, Ready-mix Concrete Establishment. Four different mixture proportions were chosen in the experimental study. 24 samples of the 4 mixtures were selected in order to set the cube compression strength. For each mixture, these 24 samples were broken down within 28 days and the characteristics of cube compression strength were obtained. After 28 days, compression strength average was found to be 50.0300 MPa. A model of Artificial Neural Network (ANN) was designed for this study and the results were obtained in this model of ANN. Both experimental and ANN data was analyzed with SPSS statistical packet software. The result of statistical analysis (p=0.9972) has been done in 95% of confidence interval. It has been seen that the ANN can be used as reliable modelling method for similar studies.en10.1145/1500879.1500924info:eu-repo/semantics/closedAccessArtificial Neural NetworkCompressive strengthSelf compacting concrete (SCC)Conference ObjectN/A