[1] K. Atanassov, Geometrical interpretation of the elements of the intuitionistic fuzzy objects,
Preprint IM-MFAIS-1-89, Sofia, 1989. Reprinted: International Journal of Bioautomation,
20(1) (2016), S43-S54.
[2] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1) (1986), 87-96.
[3] K. Atanassov, Intuitionistic fuzzy sets, International Journal of Bioautomation, 20(S1)
(2016), S27-S42.
[4] K. Atanassov, Intuitionistic Fuzzy Sets, Springer, Heidelberg, 1999.
[5] K. Atanassov, On intuitionistic fuzzy sets theory, Springer, Berlin, 8(1) (2012), 147-163.
[6] I. Bloch, Mathematical morphology on bipolar fuzzy sets: General algebraic framework, In-
ternational Journal of Approximate Reasoning, 53(7) (2012), 1031-1060.
[7] F. Chen, W. H. Xu, C. Z. Bai and X. Gao, A novel approach to guarantee good robustness
of fuzzy reasoning, Applied Soft Computing, 41(C) (2016), 224-234.
[8] R. Cignoli, I. M. L. Dottaviano and D. Mundici, Algebraic Foundations of Many-Valued
Reasoning, Kluwer Academic Publishers, Dordrecht, 2000.
[9] C. Cornelis, G. Deschrijver and E. E. Kerre, Implication in intuitionistic fuzzy and interval-
valued fuzzy set theory: construction, classification, application, International Journal of
Approximate Reasoning, 35(1) (2004), 55-95.
[10] S. S. Dai, D. W. Pei and D. Guo, Robustness analysis of full implication inference method,
International Journal of Approximate Reasoning, 54(5) (2013), 653-666.
[11] S. S. Dai, D. W. Pei and S. M. Wang, Perturbation of fuzzy sets and fuzzy reasoning based
on normalized Minkowski distances, Fuzzy Sets and Systems, 189(1) (2012), 63-73.
[12] S. Das, B. Dutta and D. Guha, Weight computation of criteria in a decision-making problem
by knowledge measure with intuitionistic fuzzy set and interval-valued intuitionistic fuzzy set,
Soft Computing, 20(9) (2016), 3421-3442.
[13] G. Deschrijver, C. Cornelis and E. E. Kerre, Class of intuitionistic fuzzy t-norms satisfying the
residuation principle, International Journal of Uncertainty Fuzziness and Knowledge-Based
Systems, 11(6) (2003), 691-709.
[14] G. Deschrijver, C. Cornelis and E. E. Kerre, On the representation of intuitionistic fuzzy
t-norms and t-conorms, IEEE Transactions on Fuzzy Systems, 12(1) (2004), 45-61.
[15] J. Y. Duan and Y. M. Li, Robustness analysis of logic metrics on F(X), International Journal
of Approximate Reasoning, 61 (2015), 33-42.
[16] D. Dubois and H. Prade, Fuzzy Sets in approximate reasoning, Fuzzy Sets and Systems,
40(1) (1991), 143-244.
[17] D. Dubois and H. Prade, Gradualness, uncertainty and bipolarity: Making sense of fuzzy
sets, Fuzzy Sets and Systems, 192(3) (2012), 3-24.
[18] F. Esteva and L. Godo, Monoidal t-norm based logic: Towards a logic for left-continuous
t-norms, Fuzzy Sets and Systems, 124(3) (2001), 271-288.
[19] C. Franco, J. Montero and J. T. Rodriguez, A fuzzy and bipolar approach to preference
modeling with application to need and desire, Fuzzy Sets and Systems, 214(1) (2013), 20-34.
[20] P. Hajek, Mathematics of Fuzzy Logic, Kluwer Academic Publishers, Dordrecht, 1998.
[21] X. X. He, K. Y. Qin and Y. F. Li, Robustness of fuzzy connectives and fuzzy reasoning, Fuzzy
Sets and Systems, 225(12) (2013), 93-105.
[22] D. H. Hong and S. Y. Hwang, A note on the value similarity of fuzzy systems variables,
Fuzzy Sets and Systems, 66(3) (1994), 383-386.
[23] C. C. Lee, Fuzzy logic in control systems: Fuzzy logic controller, IEEE Transactions on
Systems, Man, and Cybernetics, 20(2) (1990), 404-418.
[24] D. C. Li, Y. M. Li and Y. J. Xie, Robustness of interval-valued fuzzy inference, Information
Sciences, 181(20) (2011), 4754-4764.
[25] D. F. Li and C. T. Cheng, New similarity measures of intuitionistic fuzzy sets and application
to pattern recognitions, Pattern Recognition Letters, 23(1-3) (2002), 221-225.
[26] Y. F. Li, K. Y. Qin, X. X. He and D. Meng, Robustness of fuzzy connectives and fuzzy
reasoning with respect to general divergence measures, Fuzzy Sets and Systems, 294 (2016),
63-78.
[27] H. W. Liu and G. J. Wang, Continuity of triple I methods based on several implications,
Mathematical and Computer Modelling, 56(8) (2008), 2079-2087.
[28] H. W. Liu and G. J. Wang, Multi-criteria decision-making methods based on intuitionistic
fuzzy sets, European Journal of Operational Research, 179(1) (2007), 220-233.
[29] H. W. Liu and G. J. Wang, Unified forms of fully implicational restriction methods for fuzzy
reasoning, Information Sciences, 177(3) (2007), 956-966.
[30] H. W. Liu, New similarity measures between intuitionistic fuzzy sets and between elements,
Mathematical and Computer Modelling, 42(1) (2005), 61-70.
[31] R. Lowen and W. Peeters, Distances between fuzzy sets representing grey level images, Fuzzy
Sets and Systems, 99(2) (1998), 135-149.
[32] E. H. Mamdani and B. R. Gaines, Fuzzy Reasoning and its Applications, Academic Press,
London, 18(11) (1981), 1925-1935.
[33] D. W. Pei, Formalization of implication based fuzzy reasoning method, International Journal
of Approximate Reasoning, 53(5) (2012), 837-846.
[34] D. W. Pei, On equivalent forms of fuzzy logic systems NM and IMTL, Fuzzy Sets and Sys-
tems, 138(1) (2003), 187-195.
[35] D. W. Pei, On the strict logic foundation of fuzzy reasoning, Soft Computing, 8(8) (2004),
539-545.
[36] D. W. Pei, The full implication triple I algorithms and their consistency in fuzzy reasoning,
Journal of Mathematical Research and Exposition, 24(2) (2004), 359-368 (in Chinese).
[37] D. W. Pei, Unied full implication algorithms of fuzzy reasoning, Information Sciences,
178(2) (2008), 520-530.
[38] R. H. S. Reiser and B. Bedregal, Robustness on intuitionistic fuzzy connectives, Tema, 15(2)
(2014), 133-149.
[39] R. Srinivasan and S. S. Begum, Properties on Intuitionistic Fuzzy Sets of Third Type, Fuzzy
Information Processing Society, IEEE, 12(2) (2017), 189-195.
[40] Y. M. Tang and X. Z. Yang, Symmetric implicational method of fuzzy reasoning, International
Journal of Approximate Reasoning, 54(8) (2015), 1034-1048.
[41] G. J. Wang and J. Y. Duan, On robustness of the full implication triple I inference method
with respect to finer measurements, International Journal of Approximate Reasoning, 55(3)
(2014), 787-796.
[42] G. J. Wang and L. Fu, Unified forms of triple I method, Computers and Mathematics with
Applications, 49(5-6) (2005), 923-932.
[43] G. J. Wang and H. Wang, Non-fuzzy versions of fuzzy reasoning in classical logics, Informa-
tion Sciences, 138(1) (2001), 211-236.
[44] G. J. Wang, Formalized theory of general fuzzy reasoning, Information Sciences, 160(1)
(2004), 251-266.
[45] G. J. Wang, Full implicational triple I method for fuzzy reasoning, Science in China, Series
E, 29(1) (1999), 43-53.
[46] G. J. Wang, Introduction to Mathematical Logic and Resolution Principle, Science Press,
Beijing, (in Chinese), 2006.
[47] G. J. Wang, Non-classical Mathematical Logic and Approximate Reasoning, Science Press,
Beijing, (in Chinese), 2008.
[48] G. J. Wang, On the logic foundation of fuzzy reasoning, Information Sciences, 117(1-2)
(1999), 47-88.
9] L. X. Wang, A Course in Fuzzy Systems and Control, Upper Saddle River, Prentice Hall
PTR, NJ, 1997.
[50] W. H. Xu, Z. K. Xie, J. Y. Yang and Y. E. You-Pei, Continuity and approximation properties
of two classes of algorithms for fuzzy inference, Journal of Software, 15(10) (2004), (in
chinese), 1485-1492.
[51] L. A. Zadeh, Fuzzy sets, information and control, Information and Control, 8(3) (1965),
338-353.
[52] L. A. Zadeh, Generalized theory of uncertainty (GTU)-principal concepts and ideas, Com-
putational Statistics and Data Analysis, 51(1) (2006), 15-46.
[53] L. A. Zadeh, Outline of a new approach to the analysis of complex systems and decision
processes, IEEE Transactions on Systems, Man, and Cybernetics, smc-3(1) (1973), 28-44.
[54] L. A. Zadeh, Position Paper: Toward extended fuzzy logic-A first step, Fuzzy Sets and Sys-
tems, 160(21) (2009), 3175-3181.
[55] L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning,
Learning Systems and Intelligent Robots. Springer US, 8(3) (1974), 199-249.
[56] M. C. Zheng, Z. K. Shi and Y. Liu, Triple I method of approximate reasoning on Atanassov's
intuitionistic fuzzy sets, International Journal of Approximate Reasoning, 55(6) (2014), 1369-
1382.
[57] M. C. Zheng, Z. K. Shi and Y. Liu, Triple I method of intuitionistic fuzzy reasoning based
on residual implicator, Information Sciences, 43(6) (2013), (in chinese), 810-820.