Abbasi P., Mehrdadi N., Nabi R. and Zare Abyaneh H. (2013). Application of artificial neural network to predict total dissolved solids variations in groundwater of Tehran Plain, Iran. Int. J. Environ. Sustain., 2(1), 10-20.
Arumugam M. S. and Rao M. V. C. (2008). On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid systems. Appl. Soft Comput. J., 8, 324–336.
Asadollahfardi A., Taklifi Gh. and Ghanbari A. (2012). Application of artificial neural network to predict TDS in Talkheh Rud River. J. Irrig. Drain. Eng., 138(4), 363–370.
Asgari M. S., Arya Far A. and Darvari Z. (2013). Prediction of EC, TDS and TH qualitative parameters in Birjand Plain groundwater using artificial neural network. 7th Iranian Geological Engineering and Environmental Conference, Shahroud University of Technology, Semnan, Iran [In Persian].
Banejad H., Kamali M., Amirmoradi K. and Olyaie F. (2013). Forecasting some of the qualitative parameters of rivers using wavelet artificial neural network hybrid (W-ANN) model (Case of study: Jajroud River of Tehran and Gharaso River of Kermanshah). J. Health Environ., 6(3), 277-294 [In Persian].
Daryaee M., Eigder Nejad A., Bina M. and Radmanesh F. (2010). Effect of river water quality factors on EC and TDS using artificial neural networks. 8th Seminar on River Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran [In Persian].
Eberhart R. and Shi Y. (2000). Comparing inertia weights and constriction factors in particle swarm, in: Proceedings of the Congress on Evolutionary Computation, 16-19 Jul 2000, La Jolla; p. 84–88.
Gholami V., Derakhshan Sh. and Darvari Z. (2013). Investigation of multivariate regression and artificial neural network in simulation of groundwater salinity in Mazandaran Province. J. Water Res. Agri., 26(3), 353-365 [In Persian].
Kanda E. K., Kipkorir E. C. and Kosgei J. R. (2016). Dissolved oxygen modelling using artificial neural network: a case of river nzoia, lake victoria basin, kenya. J. Water Secur., 2(1), 1-7.
Hill M. (1998). Methods and guidelines for effective model calibration. U.S. Geological survey Water- Resources Investigations Rep., 98-4005.
Kurepazan A. (2004). The principles of fuzzy set theoryand its applications. Publications Amir Kabir University Jihad [In Persian].
Mirzavand M., Sadati Nrjad M. and Akbari M. (2015). Simulation Changes in groundwater quality with artificial neural network model (Case study: Kashan aquifer). Iran. J. Nat. Resour., 68 (1), 159-171 [In Persian].
Musavi-Jahromi Sh. and Golabi M. (2008). Application of artificial neural networks in the river water quality modeling: Karoon river. J. Appl. Sci., 8 (12), 2324-2328.
Minhaj M. B. (2005). Fundamentals of artificial neural networks. Amirkabir University Press [In Persian].
Nasr M. and Farouk H. (2014). Using of pH as a tool to predict salinity of groundwater for irrigation purpose using artificial neural network. Egypt. J. Aqua. Res., 40(2), 111-115.
Peeri H. and Bameri A. (2015). Estimation of sodium absorption ratio (SAR) in groundwater using multivariate linear vibration of artificial neural network (Case study of Bajestan Plain). J. Water Resour. Engi., 7(21), 67-79 [In Persian].
Poormohammadi S., Malekinezhad H. and Poorshareyati R. (2013).Comparison of ANN and time series appropriately in prediction of ground water table (Case Study: Bakhtegan basin). J. Water Soil Conserv., 20(4), 251-262 [In Persian].
Sayadi Shahraki A., Soltani Mohammadi A., Naseri A. A. and Mokhtaran A. (2017). Simulation of groundwater salinity using artificial neural network (ANN), particle swarm optimization (PSO) and model SEAWAT (Case study: Debal khazaie sugarcane plantation). J. Water Soil Conserv., 23(5), 307-316 [In Persian].
Sayadi Shahraki F. and Sayadi Shahraki A. (2019). Simulation of electrical conductivity of Behbahan Plain using ANN and ANN-PSO models. J. Water Wastewater, 4(1), 34-41 [In Persian].
Soltani Mohammadi A., Sayadi Shahraki A. and Naseri A. A. (2016). Simulation of groundwater quality parameters using ANN and ANN+PSO Models (Case Study: Ramhormoz Plain). J. Pollut., 3(2), 191-200.