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Computers and Concrete
  Volume 21, Number 1, January 2018 , pages 103-110
DOI: https://doi.org/10.12989/cac.2018.21.1.103
 


Hybrid fuzzy model to predict strength and optimum compositions of natural Alumina-Silica-based geopolymers
Ata Allah Nadiri, Somayeh Asadi, Hamed Babaizadeh and Keivan Naderi

 
Abstract
    This study introduces the supervised committee fuzzy model as a hybrid fuzzy model to predict compressive strength (CS) of geopolymers prepared from alumina-silica products. For this purpose, more than 50 experimental data that evaluated the effect of Al2O3/SiO2, Na2O/Al2O3, Na2O/H2O and Na/[Na+K] on (CS) of geopolymers were collected from the literature. Then, three different Fuzzy Logic (FL) models (Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Larsen fuzzy logic (LFL)) were adopted to overcome the inherent uncertainty of geochemical parameters and to predict CS. After validating the model, it was found that the SFL model is superior to MFL and LFL models, but each of the FL models has advantages to predict CS. Therefore, to achieve the optimal performance, the supervised committee fuzzy logic (SCFL) model was developed as a hybrid method to combine the benefits of individual FL models. The SCFL employs an artificial neural network (ANN) model to re-predict the CS of three FL model predictions. The results also show significant fitting improvement in comparison with individual FL models.
 
Key Words
    compressive strength; geopolymer; fuzzy model; Artificial Neural Network (ANN); Supervised Committee Fuzzy Logic (SCFL)
 
Address
Ata Allah Nadiri: Department of Earth Sciences, Faculty of Natural Science, University of Tabriz, 29 Bahman Boulevard, Tabriz, East Azarbaijan, Iran
Somayeh Asadi: Department of Architectural Engineering, Pennsylvania State University, 104 Engineering, Unit A, University Park, PA 16802, USA
Hamed Babaizadeh: LADOTD, 1201 Capitol Access Road, Baton Rouge, LA 70802, USA
Keivan Naderi: Department of Earth Sciences, Faculty of Natural Science, University of Tabriz, 29 Bahman Boulevard, Tabriz, East Azarbaijan, Iran
 

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