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Computers and Concrete
  Volume 21, Number 1, January 2018 , pages 21-30

Compressive strength estimation of concrete containing zeolite and diatomite: An expert system implementation
Giyasettin Ozcan, Yilmaz Kocak and Eyyup Gulbandilar

    In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days\' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.
Key Words
    expert systems; compressive strength; concrete; zeolite; diatomite
Giyasettin Ozcan: Department of Computer Engineering, Faculty of Engineering, Uludag University, Bursa, Turkey
Yilmaz Kocak: Department of Construction, Kutahya Vocational School of Technical Sciences, Dumlupinar University, Kutahya, Turkey
Eyyup Gulbandilar: Department of Computer Engineering, Faculty of Engineering and Architecture, Eskisehir Osmangazi University, Eskisehir, Turkey

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