G. Schaub, D. Unruh, J. Wang, T. Turek, Kinetic analysis of selective catalytic NOx reduction (SCR) in a catalytic filter, Chemical Engineering and Processing: Process Intensification, 42(5) (2003) 365-371.
 B. Guan, R. Zhan, H. Lin, Z. Huang, Review of state of the art technologies of selective catalytic reduction of NOx from diesel engine exhaust, Applied Thermal Engineering, 66(1) (2014) 395-414.
 G. Saracco, V. Specchia, Simultaneous removal of nitrogen oxides and fly-ash from coal-based power-plant flue gases, Applied Thermal Engineering, 18(11) (1998) 1025-1035.
 S.R. Ness, G.E. Dunham, G.F. Weber, D.K. Ludlow, SCR catalyst-coated fabric filters for simultaneous NOx and high-temperature particulate control, Environmental Progress, 14(1) (1995) 69-74.
 G. Saracco, V. Specchia, Catalytic filters for the abatement of volatile organic compounds, Chemical Engineering Science, 55(5) (2000) 897-908.
 C. Winkler, P. Flörchinger, M.D. Patil, J. Gieshoff, P. Spurk, M. Pfeifer, Modeling of SCR DeNOx Catalyst - Looking at the Impact of Substrate Attributes, SAE Transactions, 112 (2003) 691-699.
 E. Tronconi, Interaction between chemical kinetics and transport phenomena in monolithic catalysts, Catalysis Today, 34(3) (1997) 421- 427.
 Z. Lei, X. Liu, M. Jia, Modeling of selective catalytic reduction (SCR) for NO removal using monolithic honeycomb catalyst, Energy & Fuels, 23(12) (2009) 6146-6151.
 H. Xua, F. Tub, Z. Hec, J. Mad, Q. Wange, Modelling of the selective catalytic NOx reduction for diesel engine, Applied Mechanics and Materials, 71-78(2098-2102) (2011) 2098.
 L. Sharifian, Y.M. Wright, K. Boulouchos, M. Elsener, O. Kröcher, Calibration of a model for selective catalytic reduction with ammonia, including NO oxidation, and simulation of NOx reduction over an Fe–zeolite catalyst under highly transient conditions, International Journal of Engine Research, 14(2) (2012) 107- 121.
 B.K. Yun, M.Y. Kim, Modeling the selective catalytic reduction of NOx by ammonia over a Vanadia-based catalyst from heavy duty diesel exhaust gases, Applied Thermal Engineering, 50(1) (2013) 152-158.
 M. Aghbashlo, S. Hosseinpour, A.S. Mujumdar, Application of artificial neural networks (ANNs) in drying technology: A comprehensive review, Drying Technology, 33(12) (2015) 1397-1462.
 M. Mohanraj, S. Jayaraj, C. Muraleedharan, Applications of artificial neural networks for thermal analysis of heat exchangers – A review, International Journal of Thermal Sciences, 90 (2015) 150-172.
 H. Li, Z. Zhang, Z. Liu, Application of artificial neural networks for catalysis: A review, Catalysis, 7(10) (2017) 306-324.
 W.G. Baxt, Application of artificial neural networks to clinical medicine, Lancet, 346 (1995) 1135-1138.
 G. Jinescu, V. lavric, The artificial neural networks and the drying process modeling, Drying Technology, 13(5-7) (1995) 1579-1586.
 E. Assidjo, B. Yao, K. Kisselmina, D. Amané, Modeling of an industrial drying process by artificial neural networks, Brazilian Journal of Chemical Engineering, 25 (2008) 515-522.
 C. Oliveira, P. Georgieva, F. Rocha, S. Feyo de Azevedo, Artificial neural networks for modeling in reaction process systems, Neural Computing and Applications, 18(1) (2009) 15- 24.
 S. Nandi, P. Mukherjee, S.S. Tambe, R. Kumar, B.D. Kulkarni, Reaction Modeling and Optimization Using Neural Networks and Genetic Algorithms: Case Study Involving TS-1-Catalyzed Hydroxylation of Benzene, Industrial & Engineering Chemistry Research, 41(9) (2002) 2159-2169.
 A.L.N. Mota, O. Chiavone-Filho, S.S. da SilvaSyllos, E.L. Foletto, J.E.F. Moraes, C.A.O.Nascimento, Application of artificial neural network for modeling of phenol mineralization by photo-Fenton process using a multi-lamp reactor, Water Science & Technology, 69(4) (2014) 768-774.
 F. Calivá, F.S. De Ribeiro, A. Mylonakis, C. Demazi’ere, P. Vinai, G. Leontidis, S. Kollias, A Deep Learning Approach to Anomaly Detection in Nuclear Reactors, in: 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, 2018.
 M.-S. Izadkhah, A. Farzi, Mathematical and artificial neural network modeling of production of ethylene from ethane pyrolysis in a tubular reactor, Petroleum Science and Technology, 36(11) (2018) 732-738.
 C.W. Baxter, S.J. Stanley, Q. Zhang, D.W. Smith, Developing artificial neural network models of water treatment processes: a guide for utilities, Journal of Environmental Engineering and Science, 1 (2002) 201-211.
 S.S. Madaeni, G. Zahedi, M. Aminnejad, Artificial neural network modeling of O2 separation from air in a hollow fiber membrane module, Asia-Pacific Journal of Chemical Engineering, 3(4) (2008) 357-363.
 K.C. Lai, S.K. Lim, P.C. Teh, K.H. Yeap, Modeling Electrostatic Separation Process Using Artificial Neural Network (ANN), Procedia Computer Science, 91 (2016) 372- 381.
 J. Mohammadhassani, S. Khalilarya, M. Solimanpur, A. Dadvand, Prediction of NOx emissions from a direct injection diesel engine using artificial neural network, Modelling and Simulation in Engineering, 2012 (2012) 1-8.
 M. Fischer, Transient NOx estimation using artificial neural networks, IFAC Proceedings Volumes, 46(21) (2013) 101-106.
 J.D. Martínez-Morales, E.R. Palacios-Hernández, G.A. Velázquez-Carrillo, Modeling engine fuel consumption and NOx with RBF neural network and MOPSO algorithm, International Journal of Automotive Technology, 16(6) (2015) 1041-1049.
 E. Majd Faghihi, A.H. Shamekhi, Development of a neural network model for selective catalytic reduction (SCR) catalytic converter and ammonia dosing optimization using multi objective genetic algorithm, Chemical Engineering Journal, 165 (2010) 508-516.
 R. Serra, M.J. Vecchietti, E. Miró, A. Boix, In,Fe-zeolites: Active and stable catalysts for the SCR of NOx—Kinetics, characterization and deactivation studies, Catalysis Today, 133- 135 (2008) 480-486.
 W.E. Schiesser, The numerical method of lines, Academic Press, San Diego, CA, 1991.
 M. Aliramezani, C.R. Koch, R.E. Hayes, Estimating tailpipe NOx concentration using a dynamic NOx/ammonia cross sensitivity model coupled to a three state control oriented SCR model, IFAC-PapersOnLine, 49(11) (2016) 8-13.
 B. Krose, P. van der Smagt, An introduction to neural networks, 8 ed., The University of Amsterdam, Amsterdam, Netherlands, 1996.
 S.A. Hejazi, K.R. Jackson, Efficient valuation of SCR via a neural network approach, Journal of Computational and Applied Mathematics, 313 (2017) 427-439.
 K. Hubner, A. Pape, E.A. Weber, Simultaneous removal of gaseous and particulate components from gases by catalytically activated ceramic filters, in: High Temperature Gas Cleaning, 1996, pp. 267-277.