References
1. Mamdani, E.H. and Assilian, S. \An experiment in
linguistic synthesis with a fuzzy logic controller", Int.
J. Man. Mach. Stud., 7(1), pp. 1-13 (1975).
2. Takagi, T. and Sugeno, M. \Fuzzy identication of
systems and its applications to modeling and control",
IEEE Trans. Syst. Man Cybern., 15(1), pp. 116-132
(1985).
3. Kandi-D, M., Soleymani, M., and Ghadimi, A.A.
\Designing an optimal fuzzy controller for a fuel cell
vehicle considering driving patterns", Sci. Iran., 23(1),
pp. 218-227 (2016).
4. Lima, N.M.N., Li~nan, L.Z., Manenti, F., Maciel Filho,
R., Maciel, M.R.W., Embirucu, M., and Medina, L.C.
\Fuzzy cognitive approach of a molecular distillation
process", Chem. Eng. Res. Des., 89(4), pp. 471-479
(2011).
5. Lam, H.K. \A review on stability analysis
of continuous-time fuzzy-model-based control
systems: From membership-function-independent to
membership-function-dependent analysis", Eng. Appl.
Artif Intell., 67, pp. 390-408 (2018).
6. Krzywanski, J. and Nowak, W. \Modeling of bed-towall
heat transfer coecient in a large-scale CFBC by
fuzzy logic approach", Int. J. Heat Mass Transf., 94,
pp. 327-334 (2016).
7. Boulkaibet, I., Belarbi, K., Bououden, S., Marwala,
T., and Chadli, M. \A new TS fuzzy model predictive
control for nonlinear processes", Expert. Syst. Appl.,
88, pp. 132-151 (2017).
8. Kamesh, R. and Rani, K.Y. \Parameterized datadriven
fuzzy model based optimal control of a semibatch
reactor", ISA Trans., 64, pp. 418-430 (2016).
9. Esfandyari, M., Fanaei, M.A., and Zohreie, H. \Adaptive
fuzzy tuning of PID controllers", Neural Comput.
Appl., 23(1), pp. S19-S28 (2013).
10. Adoko, A.C., Gokceoglu, C., Wu, L., and Zuo, Q.J.
\Knowledge-based and data-driven fuzzy modeling for
rockburst prediction", Int. J. Rock Mech. Min. Sci.,
61, pp. 86-95 (2013).
11. Habbi, H., Zelmat, M., and Bouamama, B.O. \A dynamic
fuzzy model for a drum-boiler-turbine system",
Automatica, 39(7), pp. 1213-1219 (2003).
3390 M.H. Eghbal Ahmadi et al./Scientia Iranica, Transactions C: Chemistry and ... 25 (2018) 3381{3390
12. Sala, A., Guerra, T.M., and Babuska, R. \Perspectives
of fuzzy systems and control", Fuzzy Sets Syst., 156(3),
pp. 432-444 (2005).
13. Ahmadi, M.A. and Ebadi, M. \Fuzzy modeling and
experimental investigation of minimum miscible pressure
in gas injection process", Fluid Phase Equilib.,
378, pp. 1-12 (2014).
14. Madaeni, S.S. and Kurdian, A.R. \Fuzzy modeling and
hybrid genetic algorithm optimization of virus removal
from water using microltration membrane", Chem.
Eng. Res. Des., 89(4), pp. 456-470 (2011).
15. Amiryouse, M.R., Mohebbi, M.,
Golmohammadzadeh, S., Koocheki, A. and
Baghbani, F. \Fuzzy logic application to model
caeine release from hydrogel colloidosomes", J. Food
Eng., 212, pp. 181-189 (2017).
16. Wang, G., Luo, Z., Zhu, L., Chen, H., and Zhang,
L. \Fuzzy estimation for temperature distribution of
furnace inner surface", Int. J. Therm. Sci., 51(1), pp.
84-90 (2012).
17. Cordon, O., Gomide, F., Herrera, F., Homann, F.,
and Magdalena, L. \Ten years of genetic fuzzy systems:
Current framework and new trends", Fuzzy Sets Syst.,
141(1), pp. 5-31 (2004).
18. Herrera, F. \Genetic fuzzy systems: Taxonomy, current
research trends and prospects", Evol. Intell., 1(1),
pp. 27-46 (2008).
19. Gudwin, R., Gomide, F., and Pedrycz, W. \Context
adaptation in fuzzy processing and genetic algorithms",
Int. J. Intell. Syst., 13(10-11), pp. 929-948
(1998).
20. Cordon, O., Herrera, F., Del Jesus, M.J., Magdalena,
L., Sanchez, A.M., and Villar, P. \A multiobjective
genetic algorithm for feature selection and granularity
learning in fuzzy-rule based classication systems",
20th NAFIPS Int. Conf., 3, Vancouver, Canada, pp.
1253-1258 (2001).
21. Cordon, O., Jose del Jesus, M., and Herrera, F.
\Genetic learning of fuzzy rule-based classication
systems cooperating with fuzzy reasoning methods",
Int. J. Intell. Syst., 13(10-11), pp. 1025-1053 (1998).
22. Pulkkinen, P. and Koivisto, H. \A dynamically constrained
multiobjective genetic fuzzy system for regression
problems", IEEE Trans. Fuzzy Syst., 18(1), pp.
161-177 (2010).
23. Harmsen, G.J. \Industrial best practices of conceptual
process design", Chem. Eng. Process. Process Intensif.,
43(5), pp. 677-681 (2004).
24. Zimmermann, H.J. \Fuzzy set theory", Wiley Interdisciplinary
Reviews: Comput. Stat, 2(3). pp. 317-332
(2010).
25. Gorrini, V. and Bersini, H. \Recurrent fuzzy systems",
3rd IEEE World Conf. on Comput Intell., New
Rochelle, NY, USA, pp. 193-198 (1994).
26. Pedrycz, W. \Why triangular membership functions?",
Fuzzy Sets Syst., 64(1), pp. 21-30 (1994).
27. Sharifzadeh, M. \Integration of process design and
control: A review", Chem. Eng. Res. Des., 91(12). pp.
2515-2549 (2013).
28. Wasanapradit, T., Mukdasanit, N., Chaiyaratana, N.,
and Srinophakun, T. \Solving mixed-integer nonlinear
programming problems using improved genetic algorithms",
Korean J. Chem. Eng., 28(1), pp. 32-40
(2010).
29. Costa, L. and Oliveira, P. \Evolutionary algorithms
approach to the solution of mixed integer non-linear
programming problems", Comput. Chem. Eng., 25(2-
3), pp. 257-266 (2001).
30. Downs, J.J. and Vogel, E.F. \A plant-wide industrial
process control problem", Comput. Chem. Eng., 17(3),
pp. 245-255 (1993).