Research article

Entropy of credibility distribution for intuitionistic fuzzy variable

  • Received: 05 November 2022 Revised: 13 January 2023 Accepted: 28 January 2023 Published: 21 February 2023
  • MSC : 03E72

  • This paper handles the new information entropy measure and divergence measure associated with intuitionistic fuzzy variables (IFVs). Based on credibility distribution and credibility measure of intuitionistic fuzzy variable, the credibility entropy formulas of discrete and continuous IFVs are proposed and some of their properties are investigated. The cross-entropy of intuitionistic fuzzy variable and its relationship with credibility entropy are then discussed. Finally, some numerical examples are given to illustrate the practicability of the presented credibility entropy and cross-entropy of intuitionistic fuzzy variable. Also, we make some comparative analysis on the credibility cross-entropy measure and some existing distance measures of IFVs in the pattern recognition problem.

    Citation: Qiansheng Zhang, Jingfa Liu. Entropy of credibility distribution for intuitionistic fuzzy variable[J]. AIMS Mathematics, 2023, 8(4): 9671-9691. doi: 10.3934/math.2023488

    Related Papers:

  • This paper handles the new information entropy measure and divergence measure associated with intuitionistic fuzzy variables (IFVs). Based on credibility distribution and credibility measure of intuitionistic fuzzy variable, the credibility entropy formulas of discrete and continuous IFVs are proposed and some of their properties are investigated. The cross-entropy of intuitionistic fuzzy variable and its relationship with credibility entropy are then discussed. Finally, some numerical examples are given to illustrate the practicability of the presented credibility entropy and cross-entropy of intuitionistic fuzzy variable. Also, we make some comparative analysis on the credibility cross-entropy measure and some existing distance measures of IFVs in the pattern recognition problem.



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    [1] M. D. Ansari, A. R. Mishra, F. T. Ansari, New divergence and entropy measures for intuitionistic fuzzy sets on edge detection, Int. J. Fuzzy Syst., 20 (2018), 474–487. https://doi.org/10.1007/s40815-017-0348-4 doi: 10.1007/s40815-017-0348-4
    [2] R. Bhardwaj, A. Sharma, N. Mani, K. Kumar, An intuitionistic fuzzy entropy measure and its application in multi-attribute decision making with incomplete weights information, In: Handbook of research on advances and applications of fuzzy sets and logic, IGI Global, 2022,324–338. https://doi.org/10.4018/978-1-7998-7979-4.ch015
    [3] T. Y. Chen, C. H. Li, Determining objective weights with intuitionistic fuzzy entropy measures: a comparative analysis, Inform. Sciences, 180 (2010), 4207–4222. https://doi.org/10.1016/j.ins.2010.07.009 doi: 10.1016/j.ins.2010.07.009
    [4] A. De Luca, S. Termini, A definition of nonprobabilistic entropy in the setting of fuzzy set theory, Information and Control, 20 (1972), 301–312. https://doi.org/10.1016/S0019-9958(72)90199-4 doi: 10.1016/S0019-9958(72)90199-4
    [5] B. Farhadinia, A. I. Ban, Developing new similarity measures of generalized intuitionistic fuzzy numbers and generalized interval-valued fuzzy numbers from similarity measures of generalized fuzzy numbers, Math. Comput. Model., 57 (2013), 812–825. https://doi.org/10.1016/j.mcm.2012.09.010 doi: 10.1016/j.mcm.2012.09.010
    [6] H. Garg, Generalized intuitionistic fuzzy entropy-based approach for solving multi-attribute decision making problems with unknown attribute weights, Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci., 89 (2019), 129–139. https://doi.org/10.1007/s40010-017-0395-0 doi: 10.1007/s40010-017-0395-0
    [7] T. Garai, D. Chakraborty, T. K. Roy, Possibility-necessity-credibility measures on generalized intuitionistic fuzzy number and their applications to multi-product manufacturing system, Granul. Comput., 3 (2018), 285–299. https://doi.org/10.1007/s41066-017-0067-0 doi: 10.1007/s41066-017-0067-0
    [8] S. K. Giri, T. Garai, H. Garg, S. Islam, Possibilistic mean of generalized non-linear intuitionistic fuzzy number to solve a price and quality dependent demand multi-item inventory model, Comput. Appl. Math., 40 (2021), 1–24. https://doi.org/10.1007/s40314-021-01497-4 doi: 10.1007/s40314-021-01497-4
    [9] T. Garai, H. Garg, Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment, CAAI Trans. Intell. Technol., 4 (2019), 175–181. https://doi.org/10.1049/trit.2019.0030 doi: 10.1049/trit.2019.0030
    [10] W. L. Hung, M. S. Yang, On the J-divergence of intuitionistic fuzzy sets with its application to pattern recognition, Inform. Sciences, 178 (2008), 1641–1650. https://doi.org/10.1016/j.ins.2007.11.006 doi: 10.1016/j.ins.2007.11.006
    [11] R. Joshi, S. Kumar, An intuitionistic fuzzy (δ, γ)-norm entropy with its application in supplier selection problem, Comput. Appl. Math., 37 (2018), 5624–5649. https://doi.org/10.1007/s40314-018-0656-9 doi: 10.1007/s40314-018-0656-9
    [12] V. Lakshmana Gomathi Nayagam, J. Murugan, Triangular approximation of intuitionistic fuzzy numbers on multi-criteria decision making problem, Soft Comput., 25 (2021), 9887–9914. https://doi.org/10.1007/s00500-020-05346-0 doi: 10.1007/s00500-020-05346-0
    [13] D. F. Li, A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems, Comput. Math. Appl., 60 (2010), 1557–1570. https://doi.org/10.1016/j.camwa.2010.06.039 doi: 10.1016/j.camwa.2010.06.039
    [14] J. Liu, H. Li, B. Huang, X. Zhou, L. Zhang, Similarity-divergence intuitionistic fuzzy decision using particle swarm optimization, Appl. Soft Comput., 81 (2019), 105479. https://doi.org/10.1016/j.asoc.2019.05.006 doi: 10.1016/j.asoc.2019.05.006
    [15] P. K. Li, B. D. Liu, Entropy of credibility distributions for fuzzy variables, IEEE Trans. Fuzzy Syst., 16 (2008), 123–129. https://doi.org/10.1109/TFUZZ.2007.894975 doi: 10.1109/TFUZZ.2007.894975
    [16] B. Liu, Y. K. Liu, Expected value of fuzzy variable and fuzzy expected value models, IEEE Trans. Fuzzy Syst., 10 (2002), 445–450. https://doi.org/10.1109/TFUZZ.2002.800692 doi: 10.1109/TFUZZ.2002.800692
    [17] X. Li, Z. F. Qin, S. Kar, Mean-variance-skewness model for portfolio selection with fuzzy returns, Eur. J. Oper. Res., 202 (2010), 239–247. https://doi.org/10.1016/j.ejor.2009.05.003 doi: 10.1016/j.ejor.2009.05.003
    [18] J. Lin, Divergence measures based on the Shannon entropy, IEEE Trans. Inform. Theory, 37 (1991), 145–151. https://doi.org/10.1109/18.61115 doi: 10.1109/18.61115
    [19] A. R. Mishra, R. K. Singh, D. Motwani, Intuitionistic fuzzy divergence measure-based ELECTRE method for performance of cellular mobile telephone service providers, Neural Comput. Appl., 32 (2020), 3901–3921. https://doi.org/10.1007/s00521-018-3716-6 doi: 10.1007/s00521-018-3716-6
    [20] M. K. Mehlawat, Credibilistic mean-entropy models for multi-period portfolio selection with multi-choice aspiration levels, Inform. Sciences, 345 (2016), 9–26. https://doi.org/10.1016/j.ins.2016.01.042 doi: 10.1016/j.ins.2016.01.042
    [21] Z. F. Qin, X. Li, X. Y. Ji, Portfolio selection based on fuzzy cross-entropy, J. Comput. Appl. Math., 228 (2009), 139–149. https://doi.org/10.1016/j.cam.2008.09.010 doi: 10.1016/j.cam.2008.09.010
    [22] M. Rahimi, P. Kumar, G. Yari, Credibility measure for intuitionistic fuzzy variables, Mathematics, 6 (2018), 50. https://doi.org/10.3390/math6040050 doi: 10.3390/math6040050
    [23] E. Szmidt, J. Kacprzyk, Entropy of intuitionistic fuzzy sets, Fuzzy Set. Syst., 118 (2001), 467–477. https://doi.org/10.1016/S0165-0114(98)00402-3 doi: 10.1016/S0165-0114(98)00402-3
    [24] H. Shangguan, X. Zhang, X. Cui, Y. Liu, Q. Zhang, Z. Gui, Sinogram restoration for low-dose X-ray computed tomography using regularized Perona-Malik equation with intuitionistic fuzzy entropy, Signal, Image and Video Processing, 13 (2019), 1511–1519. https://doi.org/10.1007/s11760-019-01496-3 doi: 10.1007/s11760-019-01496-3
    [25] I. K. Vlachos, G. D. Sergiadis, Intuitionistic fuzzy information-Applications to pattern recognition, Pattern Recogn. Lett., 28 (2007), 197–206. https://doi.org/10.1016/j.patrec.2006.07.004 doi: 10.1016/j.patrec.2006.07.004
    [26] R. Verma, On intuitionistic fuzzy order-α divergence and entropy measures with MABAC method for multiple attribute group decision-making, J. Intell. Fuzzy Syst., 40 (2021), 1191–1217. https://doi.org/10.3233/JIFS-201540 doi: 10.3233/JIFS-201540
    [27] S. P. Wan, J. Y. Dong, Possibility method for triangular intuitionistic fuzzy multi-attribute group decision making with incomplete weight information, Int. J. Comput. Intell. Syst., 7 (2014), 65–79. https://doi.org/10.1080/18756891.2013.857150 doi: 10.1080/18756891.2013.857150
    [28] M. M. Xia, Z. S. Xu, Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment, Inform. Fusion, 13 (2012), 31–47. https://doi.org/10.1016/j.inffus.2010.12.001 doi: 10.1016/j.inffus.2010.12.001
    [29] T. Yogashanthi, S. Mohanaselvi, K. Ganesan, A new approach for solving flow shop scheduling roblems with generalized intuitionistic fuzzy numbers, J. Intell. Fuzzy Syst., 37 (2019), 4287–4297. https://doi.org/10.3233/JIFS-190395 doi: 10.3233/JIFS-190395
    [30] J. Ye, Multicriteria group decision-making method using vector similarity measures for trapezoidal intuitionistic fuzzy numbers, Group Decis. Negot., 21 (2012), 519–530. https://doi.org/10.1007/s10726-010-9224-4 doi: 10.1007/s10726-010-9224-4
    [31] W. Zhou, Z. S. Xu, Score-hesitation trade-off and portfolio selection under intuitionistic fuzzy environment, Int. J. Intell. Syst., 34 (2019), 325–341. https://doi.org/10.1002/int.22052 doi: 10.1002/int.22052
    [32] H. Zhou, H. Ren, A novel ranking function-based triangular intuitionistic fuzzy fault tree analysis method, J. Intell. Fuzzy Syst., 39 (2020), 2753–2761. https://doi.org/10.3233/JIFS-191018 doi: 10.3233/JIFS-191018
    [33] Q. S. Zhang, S. Y. Jiang, A note on information entropy measures for vague sets and its applications, Inform. Sciences, 178 (2008), 4184–4191. https://doi.org/10.1016/j.ins.2008.07.003 doi: 10.1016/j.ins.2008.07.003
    [34] J. Zhang, Q. Li, Credibilistic mean-semi-entropy model for multi-period portfolio selection with background risk, Entropy, 21 (2019), 944–968. https://doi.org/10.3390/e21100944 doi: 10.3390/e21100944
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