[1] Öztürk F, Apaydin H, Walling DE. Suspended sediment loads through flood events for streams of Sakarya River basin. Turkish J Eng Environ Sci 2001;25:643–50.
[2] Kuok KK, Harun S, Shamsuddin SM. Particle swarm optimization feedforward neural network for modeling runoff. Int J Environ Sci Technol 2010;7:67–78. doi:10.1007/BF03326118.
[3] Kalteh AM, Hjorth P, Berndtsson R. Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application. Environ Model Softw 2008;23:835–45. doi:10.1016/j.envsoft.2007.10.001.
[4] Guo W, Wang H. PSO optimizing neural network for the Yangtze River sediment entering estuary prediction. Proc - 2010 6th Int Conf Nat Comput ICNC 2010 2010;4:1769–72. doi:10.1109/ICNC.2010.5584412.
[5] Gholami V, Darvari Z, Mohseni Saravi M. Artificial neural network technique for rainfall temporal distribu-tion simulation (Case study: Kechik region). Casp J Environ Sci 2015;13:53–60.
[6] Chen XY, Chau KW. A Hybrid Double Feedforward Neural Network for Suspended Sediment Load Estimation. Water Resour Manag 2016;30:2179–94. doi:10.1007/s11269-016-1281-2.
[7] Kisi O, Zounemat-Kermani M. Suspended Sediment Modeling Using Neuro-Fuzzy Embedded Fuzzy c-Means Clustering Technique. Water Resour Manag 2016;30:3979–94. doi:10.1007/s11269-016-1405-8.
[8] Buyukyildiz M, Kumcu SY. An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System, Support Vector Machine and Artificial Neural Network Models. Water Resour Manag 2017;31:1343–59. doi:10.1007/s11269-017-1581-1.
[9] Harun MA, Ab Ghani A, Mohammadpour R, Chan NW. Stable channel analysis with sediment transport for rivers in Malaysia: A case study of the Muda, Kurau, and Langat rivers. Int J Sediment Res 2020;35:455–66. doi:10.1016/j.ijsrc.2020.03.008.
[10] Engineering W, Volume M, Tabatabaei M, Salehpour Jam A, Mosaffaie J. Improvement of the efficiency of artificial neural network model in suspended sediment simulation using particle swarm optimization algorithm. Watershed Eng Manag 2020;12:756–70. doi:10.22092/ijwmse.2019.125871.1638.
[11] Ebtehaj I, Bonakdari H. Assessment of evolutionary algorithms in predicting non-deposition sediment transport. Urban Water J 2016;13:499–510. doi:10.1080/1573062X.2014.994003.
[12] Adnan RM, Liang Z, El-Shafie A, Zounemat-Kermani M, Kisi O. Prediction of suspended sediment load using data-driven models. Water (Switzerland) 2019;11. doi:10.3390/w11102060.
[13] Ebtehaj I, Bonakdari H. No-Deposition Sediment Transport in Sewers Using Gene Expression Programming. J Soft Comput Civ Eng 2017;1:29–53. doi:10.22115/scce.2017.46845.
[14] Rezaie-Balf M, Attar NF, Mohammadzadeh A, Murti MA, Ahmed AN, Fai CM, et al. Physicochemical parameters data assimilation for efficient improvement of water quality index prediction: Comparative assessment of a noise suppression hybridization approach. J Clean Prod 2020;271:122576. doi:10.1016/j.jclepro.2020.122576.
[15] Tabari MMR, Soltani J. Multi-Objective Optimal Model for Conjunctive Use Management Using SGAs and NSGA-II Models. Water Resour Manag 2013;27:37–53. doi:10.1007/s11269-012-0153-7.
[16] Naderpour H, Rafiean AH, Fakharian P. Compressive strength prediction of environmentally friendly concrete using artificial neural networks. J Build Eng 2018;16:213–9. doi:10.1016/j.jobe.2018.01.007.
[17] Ghanizadeh AR, Heidarabadizadeh N, Heravi F. Gaussian process regression (Gpr) for auto-estimation of resilient modulus of stabilized base materials. J Soft Comput Civ Eng 2021;5:80–94. doi:10.22115/SCCE.2021.269187.1273.
[18] Kumar P, Pandey S, Maiti PR. A modified genetic algorithm in c++ for optimization of steel truss structures. J Soft Comput Civ Eng 2021;5:95–108. doi:10.22115/SCCE.2021.242552.1249.
[19] Darabi H, Mohamadi S, Karimidastenaei Z, Kisi O, Ehteram M, ELShafie A, et al. Prediction of daily suspended sediment load (SSL) using new optimization algorithms and soft computing models. Soft Comput 2021;25:7609–26. doi:10.1007/s00500-021-05721-5.
[20] Mirjalili S, Mirjalili SM, Lewis A. Grey Wolf Optimizer. Adv Eng Softw 2014;69:46–61. doi:10.1016/j.advengsoft.2013.12.007.
[21] Jang JSR. ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE Trans Syst Man Cybern 1993;23:665–85. doi:10.1109/21.256541.
[22] Kia E, Emadi AR, Fazlola R. Investigation and Evaluation of Artificial Neural Networks in Babolroud River Suspended Load Estimation. J Civ Eng Urban 2013;3:183–90.
[23] Pour OMR, Shui LT, Dehghani AA. Genetic algorithm model for the relation between flow discharge and suspended sediment load (Gorgan River in Iran). Electron J Geotech Eng 2011;16 E:539–53.
[24] Sattari MT, Mirabbasi R, Sushab RS, Abraham J. Prediction of Groundwater Level in Ardebil Plain Using Support Vector Regression and M5 Tree Model. Groundwater 2018;56:636–46. doi:10.1111/gwat.12620.