1. T. Oki, S. Kanae, Global hydrological cycles and world water resources, Science, 313 (2006) 1068–1072.
  2. M. Mohadesi, A. Shokri, Evaluation of Fenton and photo-Fenton processes for treatment of aqueous environment containing p-chloronitrobenzene, Desal. Water Treat., 81 (2017) 199–208.
  3. A. Shokri, the treatment of spent caustic in the wastewater of olefin units by ozonation followed by electrocoagulation process, Desal. Water Treat., 111 (2018) 173–182.
  4. A. Shokri, Degradation of 4-nitrophenol from industrial wastewater by nano catalytic ozonation, Int. J. Nano Dimens., 7 (2016) 160–167.
  5. A. Shokri, A.H. Joshaghani, Using microwave along with TiO2 for the degradation of 4-chloro-2-nitro phenol in aqueous environment, Russ. J. Appl. Chem., 89 (2016) 1985–1990.
  6. W. Choy, W. Chu, Photo-oxidation of o-chloroaniline in the presence of TiO2 and IO3: a study of photo-intermediates and successive IO2 dose, Chem. Eng. J., 136 (2008) 180–187.
  7. C. Lee, J. Yoon, Application of photo activated periodate to the decolorization of reactive dye: reaction parameters and mechanism, J. Photochem. Photobiol., A, 165 (2004) 35–41.
  8. W.A. Sadik, Effect of inorganic oxidants in photodecolourization of an azo dye, J. Photochem. Photobiol., A, 191 (2007) 132–137.
  9. J. Saien, M. Fallah Vahed Bazkiaei, Homogenous UV/periodate process in treatment of p-nitrophenol aqueous solutions under mild operating conditions, Environ. Technol., 39 (2018) 1823–1832.
  10. Z. Kim, Y. Shin, J. Yu, G. Kim, S. Hwang, Development of NOx removal process for LNG evaporation system: comparative assessment between response surface methodology (RSM) and artificial neural network (ANN), J. Ind. Eng. Chem., 74 (2019) 136–147.
  11. M.R. Gadekar, M.M. Ahammed, Modelling dye removal by adsorption onto water treatment residuals using combined response surface methodology-artificial neural network approach, J. Environ. Manage., 231 (2019) 241–248.
  12. A.M. Ghaedi, S. Karamipour, A. Vafaei, M.M. Baneshi, V. Kiarostami, Optimization and modeling of simultaneous ultrasound-assisted adsorption of ternary dyes using copper oxide nanoparticles immobilized on activated carbon using response surface methodology and artificial neural network, Ultrason. Sonochem., 51 (2019) 264–280.
  13. F.M. Elfghi, A hybrid statistical approach for modeling and optimization of RON: a comparative study and combined application of response surface methodology (RSM) and artificial neural network (ANN) based on design of experiment (DOE), Chem. Eng. Res. Des., 113 (2016) 264–272.
  14. S. Ghanavati Nasab, A. Semnani, A. Teimouri, M. Javaheran Yazd, T. Momeni Isfahani, S. Habibollahi, Decolorization of crystal violet from aqueous solutions by a novel adsorbent chitosan/nanodiopside using response surface methodology and artificial neural network-genetic algorithm, Int. J. Biol. Macromol., 124 (2019) 429–443.
  15. P. Pakravan, A. Akhbari, H. Moradi, A. Hemati Azandaryani, A.M. Mansouri, M. Safari, Process modeling and evaluation of petroleum refinery wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor using pol ethyleneimine (PEI)/titania (TiO2) multilayer film on quartz tube, Appl. Petrochem. Res., 5 (2015) 47–59.
  16. A. Shokri, Degradation of 4-chloro phenol in aqueous media thru UV/persulfate method by artificial neural network and full factorial design method, Int. J. Environ. Anal. Chem., 1 (2020) 1–15.
  17. S.N.A. Sanusi, M.I.E. Halmi, S.R.S. Abdullah, H.A. Hassan, F.M. Hamzah, M. Idrisc, Comparative process optimization of pilot-scale total petroleum hydrocarbon (TPH) degradation by Paspalum scrobiculatum L. Hackusing response surface methodology (RSM) and artificial neural networks (ANNs), Ecol. Eng., 97 (2016) 524–534.
  18. H. Li, L. Zhou, H. Lin, X. Xu, R. Jia, S. Xia, Dynamic response of biofilm microbial ecology to para-chloronitrobenzene biodegradation in a hydrogen-based, denitrifying and sulfatereducing membrane biofilm reactor, Sci. Total Environ., 643 (2018) 842–849.
  19. R. Ma, J. Shen, A. Li, Aqueous meta-chloronitrobenzene degradation by ozonation and its kinetics, Ozone Sci. Eng., 36 (2014) 496–501.
  20. J. Prakash Maren, B. Priya, Comparison of response surface methodology and artificial neural network approach towards efficient ultrasound-assisted biodiesel production from muskmelon oil, Ultrason. Sonochem., 23 (2015) 192–200.
  21. American Public Health Association, American Water Works Association, Water Pollution Control Federation, and Water Environment Federation, Standard Methods for the Examination of Water and Wastewater, Vol. 2, American Public Health Association, 1915.
  22. M. Mohadesi, A. Shokri, Treatment of oil refinery wastewater by photo-Fenton process using Box–Behnken design method: kinetic study and energy consumption, Int. J. Environ. Sci. Technol., 16 (2018) 7349–7356.
  23. M. Zarei, A. Niaei, D. Salari, A.R. Khataee, Removal of four dyes from aqueous medium by the peroxi-coagulation method using carbon nanotube–PTFE cathode and neural network modeling, J. Electroanal. Chem., 639 (2010) 167–174.
  24. H. Moradi, S. Sharifnia, F. Rahimpour, Photo catalytic decolorization of reactive yellow 84 from aqueous solutions using ZnO nanoparticles supported on mineral LECA, Mater. Chem. Phys., 158 (2015) 38–44.
  25. S. Alizadeh Kordkandi, M. Forouzesh, Application of full factorial design for methylene blue dye removal using heatactivated persulfate oxidation, J. Taiwan Inst. Chem. Eng., 45 (2014) 2597–2604.
  26. A. Shokri, Application of Sono–photo-Fenton process for degradation of phenol derivatives in petrochemical wastewater using full factorial design of experiment, Int. J. Ind. Chem., 9 (2018) 295–303.
  27. A. Shokri, Investigation of UV/H2O2 process for removal of Ortho-Toluidine from industrial wastewater by response surface methodology based on the central composite design, Desal. Water Treat., 58 (2017) 258–266.
  28. Z. Frontistis, C. Drosou, K. Tyrovola, D. Mantzavinos, D. Fatta- Kassinos, D. Venieri, N.P. Xekoukoulotakis, Experimental and modeling studies of the degradation of estrogen hormones in aqueous TiO2 suspensions under simulated solar radiation, Ind. Eng. Chem. Res., 51 (2012) 16552–16563.
  29. A.R. Khataee, M.B. Kasiri, Artificial neural networks modeling of contaminated water treatment processes by homogeneous and heterogeneous nano catalysis, J. Mol. Catal. A: Chem., 331 (2010) 86–100.
  30. C.A. Igwegbe, L. Mohmmadi., S. Ahmadi, A. Rahdar, D. Khadkhodaiy., R. Dehghani, S. Rahdar, Modeling of adsorption of Methylene Blue dye on Ho-CaWO4 nanoparticles using response surface methodology (RSM) and artificial neural network (ANN) techniques, MethodsX, 6 (2019) 1779–1797.
  31. G. Le Truong, J. De Laat, B. Legube, Effects of chloride and sulfate on the rate of oxidation of ferrous ion by H2O2, Water Res., 38 (2004) 238423–238494.
  32. C.G. Silva, J.L. Faria, Photochemical and photocatalytic degradation of an azo dye in aqueous solution by UV irradiation, J. Photochem. Photobiol., A, 155 (2003) 133–143.
  33. J. Sirvio, U. Hyvakko, H. Liimatainen, J. Niinimaki, O. Hormi, Periodate oxidation of cellulose at elevated temperatures using metal salts as cellulose activators, Carbohydr. Polym., 83 (2011) 1293–1297.