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• [1] Zadeh L.A. Fuzzy sets, Information and Control 1965; 8(3):338-353.
• [2] Atanassov K. Intuitionistic fuzzy sets, Fuzzy Sets and Systems 1986; 20 (1):87–96.
• [3] Atanassov K. More on intuitionistic fuzzy sets. Fuzzy Sets and Systems 1989; 33(1):37-45.
• [4] Pedrycz, W. Granular computing: analysis and design of intelligent systems. CRC Press; 2018.
• [5] Liu, Y., Jiang, W. A new distance measure of interval-valued intuitionistic fuzzy sets and its application in decision making. Soft Computing 2019; 1-17.
• [6] Li, D. F. Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations. Fuzzy Optimization and Decision Making 2011;10(1): 45-58.
• [7] Chen, T. Y. Interval-valued intuitionistic fuzzy QUALIFLEX method with a likelihood-based comparison approach for multiple criteria decision analysis. Information Sciences 2014; 261:149-169.
• [8] Chen, T. Y. IVIF-PROMETHEE outranking methods for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets. Fuzzy Optimization and Decision Making 2015;14(2):173-198.
• [9] Park, J. H., Cho, H. J., Kwun, Y. C. Extension of the VIKOR method for group decision making with interval-valued intuitionistic fuzzy information. Fuzzy Optimization and Decision Making 2011; 10(3): 233-253.
• [10] Kacar, S., Eksi, Z., Akgul, A., Horasan, F. MATLAB paralel hesaplama araç kutusu ile shannon entropi hesaplanmasi. 1st Internatonal Symposum on Innovatve Technologes in Engneerng and Science 2013; 765-773.
• [11] Zhang, Q. S., Jiang, S. Y., Jia, B. G., Luo, S. H. Some information measures for interval-valued intuitionistic fuzzy sets. Information Sciences 2010;180:5130–5145.
• [12] Burillo, P., Bustince, H. Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets. Fuzzy sets and systems 1996; 78(3): 305-316.
• [13] Liu, X. D., Zheng, S. H., Xiong, F. L. Entropy and subsethood for general interval-valued intuitionistic fuzzy sets. In International Conference on Fuzzy Systems and Knowledge Discovery, Springer, Berlin, Heidelberg, 2005.
• [14] Wei, C. P., Wang, P., Zhang, Y. Z. Entropy, similarity measure for inter- val-valued intuitionistic fuzzy sets and their application. Information Sciences 2011;181(19): 4273–4286.
• [15] Gao, Z.,Wei, C. Formula of interval-valued intuitionistic fuzzy entropy and its applications. Jisuanji Gongcheng yu Yingyong(Computer Engineering and Applications) 2012;48(2): 53–55.
• [16] Jin, F., Pei, L., Chen, H., Zhou, L. Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making. Knowledge-Based Systems 2014;59:132-141.
• [17] Zhang, Q., Jiang, S. Relationships between entropy and similarity measure of interval‐valued intuitionistic fuzzy sets. International Journal of Intelligent Systems 2010; 25(11):1121-1140.
• [18] De Luca, A., Termini, S. A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory. Information and control 1972; 20(4): 301-312.
• [19] Zhang, Y. J., Ma, P. J., Su, X. H., Zhang, C. P. Entropy on interval-valued intuitionistic fuzzy sets and its application in multi-attribute decision making. In Proceedings of the 14th international conference on information fusion (FUSION) 2011; 1121–1140.
• [20] Zhang, Q., Xing, H., Liu, F., Ye, J., Tang, P. Some new entropy measures for interval-valued intuitionistic fuzzy sets based on distances and their relation- ships with similarity and inclusion measures. Information Sciences 2014; 283: 55–69.
• [21] Rashid, T., Faizi, S., Zafar, S. Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making. Advances in Fuzzy Systems, 2018.
• [22] Xian, S., Dong, Y., Liu, Y., Jing, N. A novel approach for linguistic group decision making based on generalized interval‐valued intuitionistic fuzzy linguistic induced hybrid operator and TOPSIS. International Journal of Intelligent Systems 2018; 33(2): 288-314.
• [23] Tiwari, P., Gupta, P. Entropy, distance and similarity measures under interval valued intuitionistic fuzzy environment. Informatica 2018; 42:617-627.
• [24] Mishra, A. R., Rani, P., Pardasani, K. R., Mardani, A., Stević, Ž., Pamučar, D. A novel entropy and divergence measures with multi-criteria service quality assessment using interval-valued intuitionistic fuzzy TODIM method. Soft Computing, 2020; 24:11641–11661.
• [25] Ye, J. Fuzzy cross entropy of interval-valued intuitionistic fuzzy sets and its optimal decision-making method based on the weights of alternatives. Expert Systems with Applications 2011; 38(5): 6179-6183.
• [26] Chen, X., Yang, L., Wang, P., Yue, W. A fuzzy multi-criteria group decision–making method with new entropy of interval-valued intuitionistic fuzzy sets. Journal of Applied Mathematics, 2013, 1–8.
• [27] Meng, F., Tang, J. Interval‐valued intuitionistic fuzzy multiattribute group decision making based on cross entropy measure and Choquet integral. International Journal of Intelligent Systems 2013; 28(12): 1172-1195.
• [28] Zhang, Y., Li, P., Wang, Y., Ma, P., Su, X. Multiattribute decision making based on entropy under interval-valued intuitionistic fuzzy environment. Mathematical Problems in Engineering, 2013.
• [29] Wei, C., Zhang, Y. Entropy measure for interval-valued intuitionistic fuzzy sets and their application in group decision-making. Mathematical problems in engineering 2015.
• [30] Nguyen, H. A new interval-valued knowledge measure for interval-valued intuitionistic fuzzy sets and application in decision making. Expert Systems with Applications 2016; 56: 143-155.
• [31] Liu, P., Qin, X. An extended VIKOR method for decision making problem with interval-valued linguistic intuitionistic fuzzy numbers based on entropy. Informatica 2017; 28(4): 665-685.
• [32] Zhao, H., You, J. X.,Liu, H. C. Failure mode and effect analysis using MULTIMOORA method with continuous weighted entropy under interval-valued intuitionistic fuzzy environment. Soft Computing 2017; 21(18): 5355-5367.
• [33] Xu, Z. Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control Decis 2017; 22(2):215–219.
• [34] Bustince, H., Burillo, P. Correlation of interval-valued intuitionistic fuzzy sets. Fuzzy sets and systems, 1995; 74(2): 237-244.
• [35] Bustince Sola, H., Burillo López, P. A theorem for constructing interval-valued intuitionistic fuzzy sets from intuitionistic fuzzy sets. Notes on Intuitionistic Fuzzy Sets 1 1995;5-16.
• [36] Atanassov, K. T. (1994). Operators over interval valued intuitionistic fuzzy sets. Fuzzy sets and systems, 64(2), 159-174.
• [37] Xu, Z., Chen, J. On geometric aggregation over interval-valued intuitionistic fuzzy information. In Fourth international conference on fuzzy systems and knowledge discovery (FSKD 2007) 2007; 2: 466-471.
• [38] Xu, Z., Chen, J. Approach to group decision making based on interval-valued intuitionistic judgment matrices. Systems Engineering-Theory & Practice 2007;27(4):126-133.
• [39] Ye, J. Multicriteria fuzzy decision-making method using entropy weight- s-based correlation coefficients of interval-valued intuitionistic fuzzy sets. Applied Mathematical Modelling 2010; 34 (24): 3864–3870.
• [40] Sun, M., Liu, J. New entropy and similarity measures for interval-valued intuitionistic fuzzy sets. Journal of Information &Computational Science 2012; 9(18): 5799-5806.
• [41] Jing, L. Entropy and similarity measures for interval-valued intuitionistic fuzzy sets based on intuitionism and fuzziness. Advanced Modeling and Optimization 2013;15 (3): 635–643.
• [42] Chen, X., Yang, L., Wang, P., Yue, W. An effective interval-valued intuitionistic fuzzy entropy to evaluate entrepreneurship orientation of online P2P lending platforms. Advances in Mathematical Physics, 2013.
• [43] Guo, K., Song, Q. On the entropy for Atanassov's intuitionistic fuzzy sets: An interpretation from the perspective of amount of knowledge. Applied Soft Computing 2014; 24: 328-340.
• [44] Xu, J., Shen, F. A new outranking choice method for group decision making under Atanassov’s interval-valued intuitionistic fuzzy environment. Knowledge-Based Systems 2014; 70:177-188.
• [45] Zhao, N., Xu, Z. Entropy measures for interval-valued intuitionistic fuzzy information from a comparative perspective and their application to decision making. Informatica 2016; 27(1): 203-229.
• [46] Rani, P., Jain, D., Hooda, D. S. Shapley function based interval-valued intuitionistic fuzzy VIKOR technique for correlative multi-criteria decision making problems. Iranian Journal of Fuzzy Systems 2018;15(1): 25-54.
• [47] Guo, K., Zang, J. Knowledge measure for interval-valued intuitionistic fuzzy sets and its application to decision making under uncertainty. Soft Computing 2019; 23(16): 6967-6978.