Cite

[1] J. M. Mendel, Fuzzy logic systems for engineering: a tutorial, Proceedings of the IEEE, Vol.83, No.3, 1995, p.345-377.10.1109/5.364485Search in Google Scholar

[2] C. Elmas, C., O. Deperlioglu, and H. H. Sayan, Adaptive fuzzy logic controller for DC–DC converters, Expert Systems with Applications, Vol.36, No.2, 2009, pp.1540-1548.10.1016/j.eswa.2007.11.029Search in Google Scholar

[3] O. Cordn, A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems. International Journal of Approximate Reasoning, Vol. 52, No. 6, 2011, pp.894-913.10.1016/j.ijar.2011.03.004Search in Google Scholar

[4] J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, Englewood Cliffs, 1997.10.1109/TAC.1997.633847Search in Google Scholar

[5] R.E. Precup, and H. Hellendoorn, A survey on industrial applications of fuzzy control, Computers in Industry, Vol. 62, No.3, 2011, pp.213-226.10.1016/j.compind.2010.10.001Search in Google Scholar

[6] O. Cordon, F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena, Ten years of genetic fuzzy systems: current framework and new trends, Fuzzy Sets & Systems, Vol.141, No.1, 2004, pp. 5-31.10.1016/S0165-0114(03)00111-8Search in Google Scholar

[7] C. Karr, Genetic algorithms for fuzzy controllers, AI Expert, Vol.6, No. 2, 1991, pp.26-33.Search in Google Scholar

[8] B. D. Liu, C. Y. Chen, and J. Y. Tsao, Design of adaptive fuzzy logic controller based on linguistic-hedge concepts and genetic algorithms, IEEE Transactions on Systems, Man and Cybernetics, Part B: Vol.31, No.1, 2001, pp.32-53.10.1109/3477.907563Search in Google Scholar

[9] F. Herrera, M. Lozano, and J. L. Verdegay, A learning process for fuzzy control rules using genetic algorithms, Fuzzy Sets and Systems, Vol. 100, No. 1, 1998, pp.143-158.10.1016/S0165-0114(97)00043-2Search in Google Scholar

[10] T. Pal, and N. R. Pal, SOGARG: A self-organized genetic algorithm-based rule generation scheme for fuzzy controllers. IEEE Transactions on Evolutionary Computation, Vol.7, No.4, 2003, pp.397-415.10.1109/TEVC.2003.815377Search in Google Scholar

[11] E. Tunstel, and M. Jamshidi, On genetic programming of fuzzy rule-based systems for intelligent control, International Journal of Intelligent Automation and Soft Computing, Vol. 2, No. 3, 1996, pp.271-284.10.1080/10798587.1996.10750674Search in Google Scholar

[12] A. Tsakonas, Local and global optimization for Takagi–Sugeno fuzzy system by memetic genetic programming, Expert Systems with Applications, Vol.40, No.8, 2013, pp.3282-3298.10.1016/j.eswa.2012.12.099Search in Google Scholar

[13] N. Kasabov, and Q. Song, DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction, IEEE Trans. Fuzzy Systems, Vol.10, No. 2, 2002, pp.144-154.10.1109/91.995117Search in Google Scholar

[14] R. J. Contreras, M.M.B.R. Vellasco, and R. Tanscheit, Hierarchical type-2 neuro-fuzzy BSP model, Information Sciences, Vol. 181, No. 15, 2011, pp. 3210-3224.10.1016/j.ins.2011.03.019Search in Google Scholar

[15] M. P. Hinchliffe, M. J. Willis, H. Hiden, M.T. Tham, B. McKay, and G.W. Barton, Modeling chemical process systems using a multi-gene genetic programming algorithm, In: Proceedings of the First Annual Conference of Genetic Programming, J. R. Koza, MIT Press, Massachussets, 1996, pp. 56-65.Search in Google Scholar

[16] D. P. Searson, M. J. Willis, and G.A. Montague, Co-evolution of non-linear PLS model components,Journal of Chemometrics, Vol. 2, 2007, pp. 592-603.10.1002/cem.1084Search in Google Scholar

[17] F. Herrera, Genetic fuzzy systems: taxonomy, current research trends and prospects, Evolutionary Intelligence, Vol.1, No.1, 2008, pp.27-46.10.1007/s12065-007-0001-5Search in Google Scholar

[18] O. Castillo, and P. Melin, A review on the design and optimization of interval type-2 fuzzy controllers, Applied Soft Computing, Vol.12, No.4, 2012, pp.1267-1278.10.1016/j.asoc.2011.12.010Search in Google Scholar

[19] M. Fazzolari, R. Alcal, Y. Nojima, H. Ishibuchi, and F. Herrera, A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions, IEEE Transactions on Fuzzy Sets, Vol.21, No.1, 2013, pp.45-65.10.1109/TFUZZ.2012.2201338Search in Google Scholar

[20] C. F. Juang, J. Y. Lin, and C. T. Lin, Genetic reinforcement learning through symbiotic evolution for fuzzy controller design, IEEE Transactions on Systems, Man, and Cybernetics, Part B, Vol.30, No.2, 2000, pp.290-302.10.1109/3477.83637718244755Search in Google Scholar

[21] E. De Santis, A. Rizzi, A. Sadeghiany, and F. M. F. Mascioli, Genetic optimization of a fuzzy control system for energy flow management in microgrids, In: Proceedings of IFSA World Congress and NAFIPS Annual Meeting, W. Pedrycz and M. Reformat, IEEE, New Jersey, 2013, pp. 418-423.10.1109/IFSA-NAFIPS.2013.6608437Search in Google Scholar

[22] L. H. Hassan, M. Moghavvemi, H. A. Almurib, O. Steinmayer, Application of genetic algorithm in optimization of unified power flow controller parameters and its location in the power system network, International Journal of Electrical Power & Energy Systems, Vol.46, 2013, pp.89-97.10.1016/j.ijepes.2012.10.011Search in Google Scholar

[23] R. P. Prado, S. Garca-Galn, J. Exposito, and A. J. Yuste, Knowledge acquisition in fuzzy-rule-based systems with particle-swarm optimization, IEEE Transactions on Fuzzy Systems, Vol.18, No.6, 2010, pp.1083-1097.10.1109/TFUZZ.2010.2062525Search in Google Scholar

[24] O. Castillo, R. Martnez-Marroqun, P. Melin, F. Valdez, and J. Soria, Comparative study of bioinspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot, Information Sciences, Vol.192, 2012, pp.19-38.10.1016/j.ins.2010.02.022Search in Google Scholar

[25] E. Alba, C. Cotta, and J. M. Troya, Typeconstrained genetic programming for rule-base definition in fuzzy logic controllers, In: Proceedings of the First Annual Conference of Genetic Programming, J. R. Koza, MIT Press, Massachussets, 1996, pp. 255-260.Search in Google Scholar

[26] E. Tunstel, and M. Jamshidi, On genetic programming of fuzzy rule-based systems for intelligent control, International Journal of Intelligent Automation and Soft Computing, Vol.2, No.3, 1996, pp.271-284.10.1080/10798587.1996.10750674Search in Google Scholar

[27] A. Homaifar, D. Battle, E. Tunstel, and G. Dozier, Genetic Programming Design of Fuzzy Logic Controllers for Mobile Robot Path Tracking, International Journal of Knowledge Based Intelligent Engineering Systems, Vol.4, No.1, 2000, pp.33-52.Search in Google Scholar

[28] J. R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Massachusetts, 1992.Search in Google Scholar

[29] W. B. Langdon, and R. Poli, Foundations of Genetic Programming, Springer-Verlag, Heidelberg, 2002.10.1007/978-3-662-04726-2Search in Google Scholar

[30] G. J. Klir, and B. Yuan, Fuzzy sets and fuzzy logic, Prentice-Hall, New Jersey, 1995.10.1109/45.468220Search in Google Scholar

[31] T. Calvo, A. Kolesrov, M. Komornkov, and R. Mesiar, Aggregation operators: properties, classes and construction methods, In: Aggregation Operators, T. Calvo et al., Physica-Verlag, Heidelberg, 2002, pp.3-104.10.1007/978-3-7908-1787-4_1Search in Google Scholar

[32] R. R. Yager, J. Kacprzyk, and G. Beliakov, Recent developments in the ordered weighted averaging operators: theory and practice, Springer, Heidelberg, 201110.1007/978-3-642-17910-5Search in Google Scholar

[33] S. Luke and L. Panait, Lexicographic parsimony pressure, In: Proceedings of the Genetic and Evolutionary Computation Conference,W. B. Langdon et al., Morgan Kaufmann Publishers, New York, 2002, pp. 829-836.Search in Google Scholar

[34] MATLAB 7.10.0 (R2010a), The MathWorks Inc, Massachusetts, 2010.Search in Google Scholar

[35] P. R. Thrift, Fuzzy Logic Synthesis with Genetic Algorithms. In: Proceedings of the International Conference on Genetic Algorithms, R. K. Belew and L. B. Booker, Morgan Kauffman Publishers, California, pp. 509-513, July 1991.Search in Google Scholar

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