Akademik Veri Yönetim Sistemi
Celal Bayar Üniversitesi Fen Bilimleri Dergisi, cilt.18, sa.4, ss.365-369, 2022 (Hakemli Dergi)
The aim of this study is to develop an artificial intelligence that predicts the compressive strength of fly
ash substituted concretes using material mixing ratios. Within the scope of the study, 5 different fly ash
mixed concrete samples were estimated. The strength values were estimated using artificial neural
networks before the produced samples were subjected to the pressure test. In order to develop the artificial
neural network, it is introduced as a dataset of 1030 different mixing ratios consisting of experimental
results in the existing literature. In order to estimate the compressive strength, varying ratios of 8 different
materials such as water, cement, fly ash entering the mixture are analyzed. As a result of the study, it has
been observed that the predictions made using artificial neural networks are very close to the strength
values obtained from the experiments.