Abstract
Recently, it has been shown that interval type-2 fuzzy sets (IT2FSs) are more general than interval-valued fuzzy sets (IVFSs), and some of these IT2FSs can actually be non-convex. Although these IT2FSs could be considered within the general type-2 fuzzy sets’ (GT2FSs) scope, this latter have always been studied and developed under certain conditions considering the convexity and normality of their secondary grades. In recent works the operations of intersection and union for GT2FSs have been extended to include non-convex secondary grades. Hence, there is a need to develop the theory for those general forms of interval type-2 fuzzy logic systems (gfIT2FLSs) which use IT2FSs that are not equivalent to IVFSs and can have non-convex secondary grades. In this chapter, we will present the mathematical tools to define the inference engine for singleton gfIT2FLSs. This work aims to introduce the basic structure of such singleton gfIT2FLSs, paying special attention to those blocks presenting significant differences with the already well known type-2 FLSs which employ IT2FSs which are equivalent to IVFSs (we will term IVFLSs).
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References
Anzilli, L., Facchinetti, G., Mastroleo, G.: A parametric approach to evaluate fuzzy quantities. Fuzzy Sets and Syst. 250, 110–133 (2014)
Bustince, H., Fernandez, J., Hagras, H., Herrera, F., Pagola, M., Barrenechea, E.: Interval type-2 fuzzy sets are generalization of interval-valued fuzzy sets: towards a wider vie won their relationship. IEEE Trans. Fuzzy Syst. 23(5), 1876–1882 (2015)
Cara, A.B., Rojas, I., Pomares, H., Wagner, C., Hagras, H.: On comparing non-singleton type-2 and singleton type-2 fuzzy controllers for a nonlinear servo system. In: Proceedings IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems, pp. 126–133, April 2011
Coupland, S., John, R.: Geometric type-1 and type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 15, 3–15 (2007)
Figueroa, J., Posada, J., Soriano, J., Melgarejo, M., Rojas, S.: A type-2 fuzzy controller for delta parallel robot. IEEE Trans. Ind. Inf. 7(4), 661–670 (2011)
Hagras, H.: A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004)
Hernandez, P., Cubillo, S., Torres-Blanc, C.: On T-norms for type-2 fuzzy sets. IEEE Trans. Fuzzy Syst. 23(4), 1155–1163 (2014)
Hosseini, R., Qanadli, S.D., Barman, S., Mazinari, M., Ellis, T., Dehmeshki, J.: An automatic approach for learning and tuning Gaussian interval type-2 fuzzy membership functions applied to lung CAD classification system. IEEE Trans. Fuzzy Syst. 20(2), 224–234 (2012)
Jammeh, E.A., Fleury, M., Wagner, C., Hagras, H., Ghanbari, M.: Interval type-2 fuzzy logic congestion control for video streaming across IP networks. IEEE Trans. Fuzzy Syst. 17(5), 1123–1142 (2009)
Karnik, N.N., Mendel, J.M.: Type-2 fuzzy logic systems: type-reduction. In: Proceedings of the IEEE Conference on Systems, Man and Cybernetics, San Diego, CA, pp. 2046–2051, October 1998
Karnik, N.N., Mendel, J.M.: Type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 7(6), 643–658 (1999)
Karnik, N.N., Mendel, J.M.: Operations on type-2 fuzzy sets. Fuzzy Sets Syst. 122, 327–348 (2001)
Karnik, N.N., Mendel, J.M.: Centroid of a type-2 fuzzy set. Inf. Sci. 132(1), 195–220 (2001)
Liang, Q., Mendel, J.M.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5), 535–550 (2000)
Liu, F., Mendel, J.M.: An interval approach to fuzzistics for interval type-2 fuzzy sets. In: IEEE International Fuzzy Systems Conference, FUZZ-IEEE 2007, London, pp. 1–6 (2007)
Mendel, J.M.: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper-Saddle River (2001)
Mendel, J.M., Bob John, R.I.: Type-2 fuzzy sets made simple. IEEE Trans. Fuzzy Syst. 10(2), 117–127 (2002)
Mendel, J.M., John, R.I., Liu, F.: Interval type-2 fuzzy logic systems made simple. IEEE Trans. Fuzzy Syst. 14(6), 808–821 (2006)
Mendel, J.M.: Computing with words and its relationships with fuzzistics. Inf. Sci. 177(4), 988–1006 (2007)
Mendel, J.M., Liu, F., Zhai, D.: Alpha-plane representation for type-2 fuzzy sets: theory and applications. IEEE Trans. Fuzzy Syst. 17(5), 1189–1207 (2009)
Mendel, J.: On the geometry of join and meet calculations for general type-2 fuzzy sets. In: Proceedings of 2011 IEEE International Conference on Fuzzy Systems, Taiwan, pp. 2407–2413, June 2011
Mendel, J.M.: General type-2 fuzzy logic systems made simple: a tutorial. IEEE Trans. Fuzzy Syst. 22(5), 1162–1182 (2014)
Mizumoto, M., Tanaka, K.: Some properties of fuzzy sets of type 2. Inf. Control 31, 312–340 (1976)
Pomares, H., Rojas, I., Ortega, J., González, J., Prieto, A.: A systematic approach to a self-generating fuzzy rule-base for function approximation. IEEE Trans. Syst. Man Cybern. 30(3), 431–447 (2000)
Pomares, H., Rojas, I., González, J., Damas, M., Pino, B., Prieto, A.: Online global learning in direct fuzzy controllers. IEEE Trans. Fuzzy Syst. 12(2), 218–229 (2004)
Ruiz-Garcia, G., Hagras, H., Pomares, H., Rojas, I., Bustince, H.: Join and meet operations for type-2 fuzzy sets with non-convex secondary memberships. IEEE Trans. Fuzzy Syst. 24(4), 1000–1008 (2016)
Tahayori, H., Tettamanzi, A.G.B., Antoni, G.D.: Approximated type-2 fuzzy sets operations. In: Proceedings of 2006 IEEE International Conference on Fuzzy Systems, Canada, pp. 1910–1917, July 2006
Trutschnig, W., González-Rodrýguez, G., Colubi, A., Gil, M.A.: A new family of metrics for compact, convex (fuzzy) sets based on a generalized concept of mid and spread. Inf. Sci. 179, 3964–3972 (2009)
Wagner, C., Hagras, H.: Evolving type-2 fuzzy logic controllers for autonomous mobile robots. In: Melin, P., Castillo, O., Gomez Ramírez, E., Kacprzyk, J., Pedrycz, W. (eds.) Analysis and Design of Intelligent Systems using Soft Computing Techniques, vol. 41, pp. 16–25. Springer, Heidelberg (2007)
Wagner, C., Hagras, H.: Towards general type-2 fuzzy logic systems based on zSlices. IEEE Trans. Fuzzy Syst. 18(4), 637–660 (2010)
Walker, C., Walker, E.: The algebra of fuzzy truth value. Fuzzy Sets Syst. 149, 309–347 (2005)
Zadeh, L.A.: The concept of linguistic variable and its application to approximate reasoning. Inf. Sci. 8(3), 199–249 (1975)
Zhai, D., Hao, M., Mendel, J.M.: A non-singleton interval type-2 fuzzy logic system for universal image noise removal using quantum-behaved particle swarm optimization. In: Proceedings 2011 IEEE International Conference on Fuzzy Systems, pp. 957–964, June 2011
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Ruiz-García, G., Hagras, H., Rojas, I., Pomares, H. (2017). Towards a Framework for Singleton General Forms of Interval Type-2 Fuzzy Systems. In: Petrosino, A., Loia, V., Pedrycz, W. (eds) Fuzzy Logic and Soft Computing Applications. WILF 2016. Lecture Notes in Computer Science(), vol 10147. Springer, Cham. https://doi.org/10.1007/978-3-319-52962-2_1
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