Anastasakis, L. and Mort, N. (2001). The development of self-organization techniques in modelling: a review of the group method of data handling (GMDH). Research Report-University of Sheffield.
Atashkari, K, Nariman-Zadeh, N, Gölcü, M, Khalkhali, A. and Jamali, A. (2007). Modelling and multi-objective optimization of a variable valve-timing spark-ignition engine using polynomial neural networks and evolutionary algorithms. Energy Conversion and Management, 48(3), 1029-1041.
Ataie-Ashtiani, B., Baratian-Ghorghi, Z., and Beheshti, A.A. (2010). Experimental investigation of clear-water local scour of compound piers. Journal of Hydraulic Engineering, 136(6), 343-351.
Azamathulla, H.M. (2012). Gene-expression programming to predict scour at a bridge abutment. Journal of Hydroinformatics, 14(2), 324-331.
Azimi, H., Bonakdari, H., Ebtehaj, I., Gharabaghi, B., and Khoshbin, F. (2018). Evolutionary design of generalized group method of data handling-type neural network for estimating the hydraulic jump roller length. Acta Mechanica, 229(3), 1197-1214.
Azimi, H., Bonakdari, H., Ebtehaj, I., Talesh, S. H. A., Michelson, D. G., and Jamali, A. (2017). Evolutionary Pareto optimization of an ANFIS network for modeling scour at pile groups in clear water condition. Fuzzy Sets and Systems, 319, 50-69.
Azimi, H., Bonakdari, H., Ebtehaj, I., Shabanlou, S., Talesh, S. H. A., and Jamali, A. (2019). A pareto design of evolutionary hybrid optimization of ANFIS model in prediction abutment scour depth. Sādhanā, 44(7), 169.
Bateni, S. M., and Jeng, D. S. (2007). Estimation of pile group scour using adaptive neuro-fuzzy approach. Ocean Engineering, 34(8), 1344-1354.
Firat, M., and Gungor, M. (2009). Generalized regression neural networks and feed forward neural networks for prediction of scour depth around bridge piers. Advances in Engineering Software, 40(8), 731-737.
Liriano, S. L., and Day, R. A. (2001). Prediction of scour depth at culvert outlets using neural networks. Journal of Hydroinformatics, 3(4), 231-238.
Noori, R., Hoshyaripour, Gh., Ashrafi, Kh., and Nadjar Araabi B. (2010). Uncertainty analysis of developed ANN and ANFIS models in prediction of carbon monoxide daily concentration. Atmospheric Environment, 44(4), 476-482.
Shamshirband, S., Mosavi, A., and Rabczuk, T. (2020). Particle swarm optimization model to predict scour depth around a bridge pier. Frontiers of Structural and Civil Engineering, 14(4), 855-866.
Sharafi, H., Ebtehaj, I., Bonakdari, H., and Zaji, A. H. (2016). Design of a support vector machine with different kernel functions to predict scour depth around bridge piers. Natural Hazards, 84(3), 2145-2162.
Trent, R., Gagarin, N., and Rhodes, J. (1993). Estimating pier scour with artificial neural networks. In Hydraulic Engineering (pp. 1043-1048). ASCE.
Wang, H., Tang, H.W., Xiao, J.F., Wang, Y., and Jiang, S. (2016a). Clear-water local scouring around three piers in a tandem arrangement. Science China Technological Sciences, 59(6), 888–896.
Wang, H., Tang, H., Liu, Q., and Wang, Y. (2016b). Local scouring around twin bridge piers in open-channel flows. Journal of Hydraulic Engineering, 142(9), 060160081-8.