1. M.F. Akhtar, M. Ashraf, A.A. Anjum, A. Javeed, A. Sharif, A. Saleem, B. Akhtar, Textile industrial effluent induces mutagenicity and oxidative DNA damage and exploits oxidative stress biomarkers in rats, Environ. Toxicol. Pharmacol., 41 (2016) 180–186.
  2. L. Abdou, O. Hakeim, M. Mahmoud, A. El-Naggar, Comparative study between the efficiency of electron beam and gamma irradiation for treatment of dye solutions, Chem. Eng. J., 168 (2011) 752–758.
  3. V.K. Gupta, R. Jain, A. Nayak, S. Agarwal, M. Shrivastava, Removal of the hazardous dye–tartrazine by photo degradation on titanium dioxide surface, Mater. Sci. Eng. C., 31 (2011) 1062–1067.
  4. V.C. Padmanaban, M.G. Nandagopal, A. Achary, V.N. Vasudevan, N. Selvaraju, Optimisation of radiolysis of Reactive Red 120 dye in aqueous solution using ionizing 60Co gamma radiation by response surface methodology, Water Sci. Technol., 73 (2016) 3041–3048.
  5. J. Biswal, J. Paul, D. Naik, S. Sarkar, S. Sabharwal, Radiolytic degradation of 4-nitrophenol in aqueous solutions: Pulse and steady state radiolysis study, Radiation Phys. Chem., 85 (2013) 161–166.
  6. V. Padmanaban, N. Selvaraju, V. Vasudevan, A. Achary, Augmented radiolytic (60Coγ) degradation of direct red 80 (Polyazo dye): optimization, reaction kinetics and G-value interpretation, React. Kinetics Mech. Catal., 1–15.
  7. M. Wang, R. Yang, W. Wang, Z. Shen, S. Bian, Z. Zhu, Radiation- induced decomposition and decoloration of reactive dyes in the presence of H2O2, Radiation Phys. Chem., 75 (2006) 286– 291.
  8. D. Salari, A. Niaei, A. Khataee, M. Zarei, Electrochemical treatment of dye solution containing CI Basic Yellow 2 by the peroxi- coagulation method and modeling of experimental results by artificial neural networks, J. Electroanal. Chem., 629 (2009) 117–125.
  9. M.A. Behnajady, H. Eskandarloo, F. Eskandarloo, Artificial neural network modeling of the influence of sol–gel synthesis variables on the photo catalytic activity of TiO2 nanoparticles in the removal of Acid Red 27, Res. Chem. Intermed., 41 (2015) 6463–6476.
  10. M. Pirdashti, S. Curteanu, M.H. Kamangar, M.H. Hassim, M.A. Khatami, Artificial neural networks: applications in chemical engineering, Rev. Chem. Eng., 29 (2013) 205–239.
  11. G. Lenzi, R. Evangelista, E. Duarte, L. Colpini, A. Fornari, R. Menechini Neto, L. Jorge, O. Santos, Photo catalytic degradation of textile reactive dye using artificial neural network modeling approach, Desal. Water Treat., 57 (2016) 14132–14144.
  12. M. Tanzifi, M.T. Yaraki, A.D. Kiadehi, S.H. Hosseini, M. Olazar, A.K. Bhati, S. Agarwal, V.K. Gupta, A. Kazemi, Adsorption of Amido Black 10B from aqueous solution using polyaniline/SiO2 nanocomposite: Experimental investigation and artificial neural network modeling, J. Colloid Interface Sci., 510 (2018) 246–261.
  13. E. Maleki, N. Maleki, Artificial neural network modeling of Pt/C cathode degradation in PEM fuel cells, J. Electron. Mater., 45 (2016) 3822–3834.
  14. D. Salari, N. Daneshvar, F. Aghazadeh, A. Khataee, Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process, J. Hazard. Mater., 125 (2005) 205–210.
  15. N. Daneshvar, A. Khataee, N. Djafarzadeh, The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing CI Basic Yellow 28 by electro coagulation process, J. Hazard. Mater., 137 (2006) 1788–1795.
  16. D.N. Kartic, B.C.A. Narayana, M. Arivazhagan, Removal of high concentration of sulfate from pigment industry effluent by chemical precipitation using barium chloride: RSM and ANN modeling approach, J. Environ. Manage., 206 (2018) 69–76.
  17. K. Yetilmezsoy, S. Demirel, Artificial neural network (ANN) approach for modeling of Pb (II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells, J. Hazard. Mater., 153 (2008) 1288–1300.
  18. G.D. Garson, Interpreting neural-network connection weights, AI expert., 6 (1991) 46–51.
  19. C.C. Guaratini, A.G. Fogg, M.V.B. Zanoni, Assessment of the application of cathodic stripping voltammetry to the analysis of diazo reactive dyes and their hydrolysis products, Dyes Pigments, 50 (2001) 211–221.
  20. E.S. Elmolla, M. Chaudhuri, M.M. Eltoukhy, The use of artificial neural network (ANN) for modeling of COD removal from antibiotic aqueous solution by the Fenton process, J. Hazard. Mater., 179 (2010) 127–134.
  21. A.A. Basfar, H.M. Khan, A.A. Al-Shahrani, Trihalomethane treatment using gamma irradiation: kinetic modeling of single solute and mixtures, Radiation Phys. Chem., 72 (2005) 555–563.
  22. Z. Guo, Q. Dong, D. He, C. Zhang, Gamma radiation for treatment of bisphenol A solution in presence of different additives, Chem. Eng. J., 183 (2012) 10–14.
  23. N. Suzuki, T. Nagai, H. Hotta, M. Washino, The radiation-induced degradation of azo dyes in aqueous solutions, Int. J. Appl. Radiation Isotopes, 26 (1975) 726–730.
  24. A. Swallow, In: J.H. Baxendale, F. Busi, The study of fast processes and transient species by electron pulse radiolysis, Springer 1982, pp. 289–315.