TY  - JOUR
TI  - Estimating the Compressive Strength of Fly Ash Added Concrete Using Artificial Neural Networks
AB  - 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.
AU  - Gurbuz, Ali
AU  - Ustabas, Ilker
AU  - KURT, ZAFER
AU  - ÇAKMAK, TALİP
DO  - 10.18466/cbayarfbe.1064779
PY  - 2022
JO  - Celal Bayar Üniversitesi Fen Bilimleri Dergisi
VL  - 18
IS  - 4
SN  - 1305-130X
SP  - 365
EP  - 369
DB  - TRDizin
UR  - http://search/yayin/detay/1144892
ER  -