[1] Baczyński, M., Jayaram, B.: (S,N)- and R-implications: A state-of-the-art survey. Fuzzy Set Syst. 159 (2008), 1836-1859. DOI 10.1016/j.fss.2007.11.015 | MR 2428086

[2] Baczyński, M., Jayaram, B.: Fuzzy implications (Studies in Fuzziness and Soft Computing, Vol. 231. Springer, Berlin Heidelberg 2008. MR 2428086

[3] Chaudhuria, B. B., Rosenfeldb, A.: A modified Hausdorff distance between fuzzy sets. Inform. Sci. 118 (1999), 159-171. DOI 10.1016/s0020-0255(99)00037-7 | MR 1723219

[4] Dai, S. S., Pei, D. W., Wang, S. M.: Perturbation of fuzzy sets and fuzzy reasoning based on normalized Minkowski distances. Fuzzy Set Syst. 189 (2012), 63-73. DOI 10.1016/j.fss.2011.07.012 | MR 2871353

[5] Dai, S. S., Pei, D. W., Guo, D. H.: Robustness analysis of full implication inference method. Int. J. Approx. Reason. 54 (2013), 653-666. DOI 10.1016/j.ijar.2012.11.007 | MR 3041100

[6] Liu, F., Zhang, W. G., Fu, J. H.: A new method of obtaining the priority weights from an interval fuzzy preference relation. Inform. Sci. 185 (2012), 32-42. DOI 10.1016/j.ins.2011.09.019

[7] Liu, F., Zhang, W. G., Wang, Z. X.: A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making. Eur. J. Oper. Res. 218 (2012), 747-754. DOI 10.1016/j.ejor.2011.11.042 | MR 2881747

[8] Fodor, J. C.: Contrapositive symmetry of fuzzy implications. Fuzzy Set Syst. 69 (1995), 141-156. DOI 10.1016/0165-0114(94)00210-x | MR 1317882

[9] Fodor, J., Roubens, M.: Fuzzy Preference Modeling and Multicriteria Decision Support. Kluwer Academic Publishers, Dordrecht, 1994. DOI 10.1007/978-94-017-1648-2

[10] Gottwald, S.: A Treatise on Many-Valued Logics. Research Studies, Studies in Logic and Computation 9, Baldock 2001. MR 1856623 | Zbl 1048.03002

[11] Guo, F. F., Chen, T. Y., Xia, Z. Q.: Triple I methods for fuzzy reasoning based on maximum fuzzy entropy principle. Fuzzy Syst. Math. 17 (2003), 55-59. MR 2026787

[12] Hong, D. H., Hwang, S. Y.: A note on the value similarity of fuzzy systems variable. Fuzzy Set Syst. 66 (1994), 383-386. DOI 10.1016/0165-0114(94)90107-4 | MR 1300296

[13] Jayaram, B.: On the law of importation $(x\wedge y) \rightarrow z \equiv (x\rightarrow (y\rightarrow z))$ in fuzzy logic. IEEE Trans. Fuzzy Syst. 16 (2008), 130-144. DOI 10.1109/tfuzz.2007.895969

[14] Jaynes, E. T.: Where do we stand on maximum entropy?. In: The Maximum Entropy Formalism (R. .D. Levine and M. Tribus, eds.), MIT Press, Cambridge 1978, pp. 15-118. MR 0521743

[15] Jaynes, E. T.: On the rationale of maximum-entropy methods. Proc. IEEE, 70 (1982), 939-952. DOI 10.1109/proc.1982.12425

[16] Jenei, S.: Continuity on Zadeh's compositional rule of inference. Fuzzy Set Syst. 104 (1999), 333-339. DOI 10.1016/s0165-0114(97)00198-x | MR 1688064

[17] Klement, E. P., Mesiar, R., Pap, E.: Triangular Norms. Kluwer Academic Publishers, Dordrecht 2000. DOI 10.1007/978-94-015-9540-7 | MR 1790096 | Zbl 1087.20041

[18] Li, H. X.: Probability representations of fuzzy systems. Sci. China Ser. F-Inf. Sci. 49 (2006), 339-363. DOI 10.1007/s11432-006-0339-9 | MR 2250341

[19] Li, H., Lee, E. S.: Interpolation representations of fuzzy logic systems. Comput. Math. Appl. 45 (2003), 1683-1693. DOI 10.1016/s0898-1221(03)00147-0 | MR 1993238

[20] Luo, M. X., Liu, B.: Robustness of interval-valued fuzzy inference triple I algorithms based on normalized Minkowski distance. J. Log. Algebr. Methods 86 (2017), 298-307. DOI 10.1016/j.jlamp.2016.09.006 | MR 3575372

[21] Mas, M., Monserrat, M., Torrens, J., Trillas, E.: A survey on fuzzy implication functions. IEEE Trans. Fuzzy Syst. 15 (2007), 1107-1121. DOI 10.1109/tfuzz.2007.896304

[22] Novák, V., Perfilieva, I., Močkoř, J.: Mathematical Principles of Fuzzy Logic. Kluwer Academic Publishes, Boston, Dordrecht 1999. DOI 10.1007/978-1-4615-5217-8 | MR 1733839 | Zbl 0940.03028

[23] Pang, L. M., Tay, K. M., Lim, C. P.: Monotone fuzzy rule relabeling for the zero-order TSK fuzzy inference system. IEEE Trans. Fuzzy Syst. 24 (2016), 1455-1463. DOI 10.1109/tfuzz.2016.2540059

[24] Pedrycz, W.: Granular Computing: Analysis and Design of Intelligent Systems. CRC Press/Francis and Taylor, Boca Raton 2013.

[25] Pedrycz, W.: From fuzzy data analysis and fuzzy regression to granular fuzzy data analysis. Fuzzy Set Syst. 274 (2015), 12-17. DOI 10.1201/9781315216737 | MR 3355341

[26] Pedrycz, W., Wang, X. M.: Designing fuzzy sets with the use of the parametric principle of justifiable granularity. IEEE Trans. Fuzzy Syst. 24 (2016), 489-496. DOI 10.1109/tfuzz.2015.2453393

[27] Pei, D. W.: $R_{0}$ implication: characteristics and applications. Fuzzy Set Syst. 131 (2002), 297-302. DOI 10.1016/s0165-0114(02)00053-2 | MR 1939842

[28] Pei, D. W.: Unified full implication algorithms of fuzzy reasoning. Inform. Sci. 178 (2008), 520-530. DOI 10.1016/j.ins.2007.09.003 | MR 2363234

[29] Rosenfeld, A.: Distances between fuzzy sets. Pattern Recogn. Lett. 3 (1985), 229-233. DOI 10.1016/0167-8655(85)90002-9

[30] Sarkoci, P., Šabo, M.: Information boundedness principle in fuzzy inference process. Kybernetika 38 (2002), 327-338. MR 1944313

[31] Szmidt, E., Kacprzyk, J.: Entropy for intuitionistic fuzzy sets. Fuzzy Set Syst. 118 (2001), 467-477. DOI 10.1016/s0165-0114(98)00402-3 | MR 1809394 | Zbl 1045.94007

[32] Tang, Y. M.: Differently implicational hierarchical inference algorithm under interval-valued fuzzy environment. In: Proc. 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), Istanbul, pp. 1-8. DOI 10.1109/fuzz-ieee.2015.7337944 | MR 3324890

[33] Tang, Y. M., Liu, X. P.: Differently implicational universal triple I method of (1, 2, 2) type. Comput. Math. Appl. 59 (2010), 1965-1984. DOI 10.1016/j.camwa.2009.11.016 | MR 2595972

[34] Tang, Y. M., Ren, F. J.: Universal triple I method for fuzzy reasoning and fuzzy controller. Iran. J. Fuzzy Syst. 10 (2013), 1-24. DOI 10.1109/fskd.2013.6816179 | MR 3154637

[35] Tang, Y. M., Ren, F. J.: Variable differently implicational algorithm of fuzzy inference. J. Intell. Fuzzy Syst. 28 (2015), 1885-1897. DOI 10.3233/IFS-141476 | MR 3324890

[36] Tang, Y. M., Ren, F. J.: Fuzzy systems based on universal triple I method and their response functions. Int. J. Inf. Tech. Decis. 16 (2017), 443-471. DOI 10.1142/s0219622014500746

[37] Tang, Y. M., Ren, F. J., Chen, Y. X.: Differently implicational $\alpha$-universal triple I restriction method of (1, 2, 2) type. J. Syst. Eng. Electron. 23 (2012), 560-573. DOI 10.1109/jsee.2012.00070

[38] Tang, Y. M., Yang, X. Z.: Symmetric implicational method of fuzzy reasoning. Int. J. Approx. Reason. 54 (2013), 1034-1048. DOI 10.1016/j.ijar.2013.04.012 | MR 3081298

[39] Tang, Y. M., Yang, X. Z., Yue, F.: Universal triple I method with maximum fuzzy entropy employing R-implications. In: Proc. the 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2013), pp. 125-129. DOI 10.1109/fskd.2013.6816179

[40] Wang, L. X.: A Course in Fuzzy Systems and Control. Prentice-Hall, Englewood Cliffs, NJ, 1997.

[41] Wang, G. J.: On the logic foundation of fuzzy reasoning. Inform. Sci. 117 (1999), 47-88. DOI 10.1016/s0020-0255(98)10103-2 | MR 1705095

[42] Wang, G. J., Fu, L.: Unified forms of triple I method. Comput. Math. Appl. 49 (2005), 923-932. DOI 10.1016/j.camwa.2004.01.019 | MR 2135223

[43] Wang, G. J., Zhou, H. J.: Introduction to Mathematical Logic and Resolution Principle. Co-published by Science Press and Alpha International Science Ltd., 2009.

[44] Yang, X. Y., Yu, F. S., Pedrycz, W.: Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system. Int. J. Approx. Reasoning 81 (2017), 1-27. DOI 10.1016/j.ijar.2016.10.010 | MR 3589730

[45] Zadeh, L. A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cyber. 3 (1973), 28-44. DOI 10.1109/tsmc.1973.5408575 | MR 0309582