B. Behforouz, P. Memarzadeh, M. Eftekhar, F. Fathi, Regression and ANN models for durability and mechanical characteristics of waste ceramic powder high performance sustainable concrete, Computers and Concrete 25(2) (2020) 119-132.
 M. Batayneh, I. Marie, I. Asi, Use of selected waste materials in concrete mixes, Waste management 27(12) (2007) 1870-1876.
 M. Carsana, M. Frassoni, L. Bertolini, Comparison of ground waste glass with other supplementary cementitious materials, Cement and Concrete Composites 45 (2014) 39-45.
 A. Mansoori, M.M. Moein, E. Mohseni, Effect of micro silica on fiber-reinforced self-compacting composites containing ceramic waste, Journal of Composite Materials (2020).
 N. Ay, M. Ünal, The use of waste ceramic tile in cement production, Cement and Concrete Research 30(3) (2000) 497-499.
 D.J. Anderson, S.T. Smith, F.T. Au, Mechanical properties of concrete utilising waste ceramic as coarse aggregate, Construction and Building Materials 117 (2016) 20-28.
 F. Pacheco-Torgal, S. Jalali, Reusing ceramic wastes in concrete, Construction and Building Materials 24(5) (2010) 832-838.
 A. Heidari, D. Tavakoli, A study of the mechanical properties of ground ceramic powder concrete incorporating nano-SiO2 particles, Construction and Building Materials 38 (2013) 255-264.
 D.M. Kannan, S.H. Aboubakr, A.S. El-Dieb, M.M.R. Taha, High performance concrete incorporating ceramic waste powder as large partial replacement of Portland cement, Construction and Building Materials 144 (2017) 35-41.
 J. Sobhani, M. Najimi, A.R. Pourkhorshidi, T. Parhizkar, Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models, Construction and Building Materials 24(5) (2010) 709-718.
 H. Naderpour, M. Mirrashid, Shear failure capacity prediction of concrete beam–column joints in terms of ANFIS and GMDH, Practice Periodical on Structural Design and Construction 24(2) (2019) 04019006.
 S.-C. Lee, Prediction of concrete strength using artificial neural networks, Engineering structures 25(7) (2003) 849-857.
 K.O. Akande, T.O. Owolabi, S. Twaha, S.O. Olatunji, Performance comparison of SVM and ANN in predicting compressive strength of concrete, IOSR Journal of Computer Engineering 16(5) (2014) 88-94.
 F. Khademi, M. Akbari, S.M. Jamal, M. Nikoo, Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete, Frontiers of Structural and Civil Engineering 11(1) (2017) 90-99.
 F. Khademi, S.M. Jamal, Estimating the compressive strength of concrete using multiple linear regression and adaptive neuro-fuzzy inference system, International Journal of Structural Engineering 8(1) (2017) 20-31.
 S.M. Mousavi, P. Aminian, A.H. Gandomi, A.H. Alavi, H. Bolandi, A new predictive model for compressive strength of HPC using gene expression programming, Advances in Engineering Software 45(1) (2012) 105-114.
 A. Mollahasani, A.H. Alavi, A.H. Gandomi, Empirical modeling of plate load test moduli of soil via gene expression programming, Computers and Geotechnics 38(2) (2011) 281-286.
 A.H. Gandomi, A.H. Alavi, M.G. Sahab, New formulation for compressive strength of CFRP confined concrete cylinders using linear genetic programming, Materials and Structures 43(7) (2010) 963-983.
 P. Sarir, J. Chen, P.G. Asteris, D.J. Armaghani, M. Tahir, Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns, Engineering with Computers (2019) 1-19.
 A.A. Shahmansouri, H.A. Bengar, E. Jahani, Predicting compressive strength and electrical resistivity of eco-friendly concrete containing natural zeolite via GEP algorithm, Construction and Building Materials 229 (2019) 116883.
 A.A. Shahmansouri, H.A. Bengar, S. Ghanbari, Compressive strength prediction of eco-efficient GGBS-based geopolymer concrete using GEP method, Journal of Building Engineering (2020) 101326.
 M. Nematzadeh, A.A. Shahmansouri, M. Fakoor, Post-fire compressive strength of recycled PET aggregate concrete reinforced with steel fibers: Optimization and prediction via RSM and GEP, Construction and Building Materials 252 (2020) 119057.
 S. Fakhrian, H. Behbahani, S. Mashhadi, Predicting post-fire behavior of green geopolymer mortar containing recycled concrete aggregate via GEP approach, Journal of Soft Computing in Civil Engineering 4(2) (2020) 22-45.
 M.F. Javed, M.N. Amin, M.I. Shah, K. Khan, B. Iftikhar, F. Farooq, F. Aslam, R. Alyousef, H. Alabduljabbar, Applications of gene expression programming and regression techniques for estimating compressive strength of bagasse ash based concrete, Crystals 10(9) (2020) 737.
 X.-Y. Wang, Prediction of flexural strength of natural pozzolana and limestone blended concrete using machine learning based models, MS&E 784(1) (2020) 012005.
 F. Ameri, P. Shoaei, S.A. Zareei, B. Behforouz, Geopolymers vs. alkali-activated materials (AAMs): A comparative study on durability, microstructure, and resistance to elevated temperatures of lightweight mortars, Construction and Building Materials 222 (2019) 49-63.
 D. Nasr, B. Behforouz, P.R. Borujeni, S.A. Borujeni, B. Zehtab, Effect of nano-silica on mechanical properties and durability of self-compacting mortar containing natural zeolite: Experimental investigations and artificial neural network modeling, Construction and Building Materials 229 (2019) 116888.
 A.A. Shahmansouri, H.A. Bengar, H. AzariJafari, Life cycle assessment of eco-friendly concrete mixtures incorporating natural zeolite in sulfate-aggressive environment, Construction and Building Materials 268 (2021) 121136.
 M. Nematzadeh, A.A. Shahmansouri, R. Zabihi, Innovative models for predicting post-fire bond behavior of steel rebar embedded in steel fiber reinforced rubberized concrete using soft computing methods, Structures, Elsevier, 2021, pp. 1141-1162.
 A.A. Shahmansouri, M. Nematzadeh, A. Behnood, Mechanical properties of GGBFS-based geopolymer concrete incorporating natural zeolite and silica fume with an optimum design using response surface method, Journal of Building Engineering 36 (2021) 102138.
 A.A. Shahmansouri, H. Akbarzadeh Bengar, S. Ghanbari, Experimental investigation and predictive modeling of compressive strength of pozzolanic geopolymer concrete using gene expression programming, Journal of Concrete Structures and Materials 5(1) (2020) 92-117.