Up to now, the entropy of uncertain sets has found many applications in areas including uncertain finance, uncertain inference, and learning curves. Providing a maximum entropy principle for uncertain sets is helpful for selecting appropriate membership functions in these areas. This paper proposes the maximum entropy principle for uncertain sets and obtains the membership function which achieves the maximum entropy by using the Euler equation in the calculus of variations. Additionally, the entropy of some commonly used uncertain sets is computed in the manuscript.
Citation: Chenyan Liu, Guanzhong Ma. Maximum entropy principle for uncertain sets with expectation and variance constraints[J]. AIMS Mathematics, 2026, 11(4): 9303-9318. doi: 10.3934/math.2026384
Up to now, the entropy of uncertain sets has found many applications in areas including uncertain finance, uncertain inference, and learning curves. Providing a maximum entropy principle for uncertain sets is helpful for selecting appropriate membership functions in these areas. This paper proposes the maximum entropy principle for uncertain sets and obtains the membership function which achieves the maximum entropy by using the Euler equation in the calculus of variations. Additionally, the entropy of some commonly used uncertain sets is computed in the manuscript.
| [1] | B. D. Liu, Uncertainty theory, 2 Eds., Berlin, Heidelberg: Springer, 2007. https://doi.org/10.1007/978-3-540-73165-8 |
| [2] |
T. Q. Ye, B. D. Liu, Uncertain hypothesis test for uncertain differential equations, Fuzzy Optim. Decis. Mak., 22 (2023), 195–211. https://doi.org/10.1007/s10700-022-09389-w doi: 10.1007/s10700-022-09389-w
|
| [3] |
Y. Liu, B. D. Liu, A modified uncertain maximum likelihood estimation with applications in uncertain statistics, Comm. Statist. Theory Methods, 53 (2024), 6649–6670. https://doi.org/10.1080/03610926.2023.2248534 doi: 10.1080/03610926.2023.2248534
|
| [4] |
B. D. Liu, X. W. Chen, Uncertain multiobjective programming and uncertain goal programming, J. Uncertain. Anal. Appl., 3 (2015), 10. https://doi.org/10.1186/s40467-015-0036-6 doi: 10.1186/s40467-015-0036-6
|
| [5] |
R. Gao, Y. B. Ma, Uncertain random bilevel programming models and their application to shared capacity routing problem, J. Comput. Appl. Math., 423 (2023), 114965. https://doi.org/10.1016/j.cam.2022.114965 doi: 10.1016/j.cam.2022.114965
|
| [6] |
J. W. Gao, K. Yao, J. Zhou, H. Ke, Reliability analysis of uncertain weighted $k$-out-of-$n$ systems, IEEE Trans. Fuzzy Syst., 26 (2018), 2663–2671. https://doi.org/10.1109/TFUZZ.2018.2806365 doi: 10.1109/TFUZZ.2018.2806365
|
| [7] |
Z. G. Zeng, R. Kang, M. Wen, E. Zio, Uncertainty theory as a basis for belief reliability, Inform. Sci., 429 (2018), 26–36. https://doi.org/10.1016/j.ins.2017.10.050 doi: 10.1016/j.ins.2017.10.050
|
| [8] |
Z. Liu, S. K. Yang, M. H. Yang, R. Kang, Software belief reliability growth model based on uncertain differential equation, IEEE Trans. Reliab., 71 (2022), 775–787. https://doi.org/10.1109/TR.2022.3154770 doi: 10.1109/TR.2022.3154770
|
| [9] |
Y. Zhang, J. W. Gao, Z. F. Fu, Valuing currency swap contracts in uncertain financial market, Fuzzy Optim. Decis. Mak., 18 (2019), 15–35. https://doi.org/10.1007/s10700-018-9284-5 doi: 10.1007/s10700-018-9284-5
|
| [10] |
Y. Liu, W. Lio, Power option pricing problem of uncertain exponential Ornstein-Uhlenbeck model, Chaos Solitons Fract., 178 (2024), 114293. https://doi.org/10.1016/j.chaos.2023.114293 doi: 10.1016/j.chaos.2023.114293
|
| [11] |
Y. H. Liu, D. A. Ralescu, Expected loss of uncertain random systems, Soft Comput., 22 (2018), 5573–5578. https://doi.org/10.1007/s00500-017-2510-1 doi: 10.1007/s00500-017-2510-1
|
| [12] | B. D. Liu, Uncertain set theory and uncertain inference rule with application to uncertain control, J. Uncertain Syst., 4 (2010), 83–98. |
| [13] |
L. A. Zadeh, Fuzzy sets, Inform. Control, 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X doi: 10.1016/S0019-9958(65)90241-X
|
| [14] |
G. M. Tan, X. C. Yu, Hyperbolic entropy of uncertain sets and its applications, J. Intell. Fuzzy Syst., 45 (2023), 1155–1168. https://doi.org/10.3233/JIFS-223626 doi: 10.3233/JIFS-223626
|
| [15] |
C. G. Wang, G. Shi, Y. H. Sheng, H. Ahmadzade, Exponential entropy of uncertain sets and its applications to learning curve and portfolio optimization, J. Ind. Manag. Optim., 21 (2025), 1488–1502. https://doi.org/10.3934/jimo.2024134 doi: 10.3934/jimo.2024134
|
| [16] |
X. Gao, Y. Gao, D. A. Ralescu, On Liu's inference rule for uncertain systems, Internat. J. Uncertain. Fuzziness Knowledge Based Systems, 18 (2010), 1–11. https://doi.org/10.1142/S0218488510006349 doi: 10.1142/S0218488510006349
|
| [17] |
Y. Gao, Uncertain inference control for balancing an inverted pendulum, Fuzzy Optim. Decis. Mak., 11 (2012), 481–492. https://doi.org/10.1007/s10700-012-9124-y doi: 10.1007/s10700-012-9124-y
|
| [18] |
X. W. Chen, D. A. Ralescu, A note on truth value in uncertain logic, Expert Syst. Appl., 38 (2011), 15582–15586. https://doi.org/10.1016/j.eswa.2011.05.030 doi: 10.1016/j.eswa.2011.05.030
|
| [19] |
C. E. Shannon, A mathematical theory of communication, Bell Syst. Tech. J., 27 (1948), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x doi: 10.1002/j.1538-7305.1948.tb01338.x
|
| [20] | R. M. Gray, Entropy and information theory, New York: Springer, 2011. https://doi.org/10.1007/978-1-4419-7970-4 |
| [21] | A. N. Kolmogorov, A new metric invariant of transitive dynamical systems and endomorphisms of Lebesgue spaces, Dokl. Russ. Acad. Sci., 119 (1958), 861–864. |
| [22] | B. D. Liu, Uncertain logic for modeling human language, J. Uncertain Syst., 5 (2011), 3–20. |
| [23] | M. Einsiedler, T. Ward, Ergodic theory, London: Springer, 2011. https://doi.org/10.1007/978-0-85729-021-2 |
| [24] | N. F. G. Martin, J. W. England, Mathematical theory of entropy, Cambridge University Press, 2013. https://doi.org/10.1017/CBO9781107340718 |
| [25] | P. Walters, An introduction to ergodic theory, New York: Springer, 2000. |
| [26] | B. D. Liu, Uncertainty theory, 4 Eds., Berlin, Heidelberg: Springer, 2015. https://doi.org/10.1007/978-3-662-44354-5 |
| [27] |
E. T. Jaynes, Information theory and statistical mechanics, Phys. Rev., 106 (1957), 620. https://doi.org/10.1103/PhysRev.106.620 doi: 10.1103/PhysRev.106.620
|
| [28] |
E. T. Jaynes, Information theory and statistical mechanics. Ⅱ, Phys. Rev., 108 (1957), 171. https://doi.org/10.1103/PhysRev.108.171 doi: 10.1103/PhysRev.108.171
|
| [29] |
J. J. Buckley, Entropy principles in decision making under risk, Risk Anal., 5 (1985), 303–313. https://doi.org/10.1111/j.1539-6924.1985.tb00186.x doi: 10.1111/j.1539-6924.1985.tb00186.x
|
| [30] |
M. P. Hoefer, S. B. Ahmed, The maximum entropy principle in decision making under uncertainty: special cases applicable to developing technologies, Amer. J. Math. Management Sci., 10 (1990), 261–273. https://doi.org/10.1080/01966324.1990.10737285 doi: 10.1080/01966324.1990.10737285
|
| [31] | P. S. Naidu, Modern spectrum analysis of time series, CRC Press, 1996. |
| [32] |
B. Clarke, Information optimality and Bayesian modelling, J. Econom., 138 (2007), 405–429. https://doi.org/10.1016/j.jeconom.2006.05.003 doi: 10.1016/j.jeconom.2006.05.003
|
| [33] | A. Polpo, J. Stern, F. Louzada, R. Izbicki, H. Takada, Bayesian inference and maximum entropy methods in science and engineering, Cham: Springer, 2018. https://doi.org/10.1007/978-3-319-91143-4 |
| [34] |
Y. M. Zhang, Principle of maximum entropy for reliability analysis in the design of machine components, Front. Mech. Eng., 14 (2019), 21–32. https://doi.org/10.1007/s11465-018-0512-z doi: 10.1007/s11465-018-0512-z
|
| [35] |
T. P. Zu, R. Kang, M. Wen, Q. Y. Zhang, Belief reliability distribution based on maximum entropy principle, IEEE Access, 6 (2017), 1577–1582. https://doi.org/10.1109/ACCESS.2017.2779475 doi: 10.1109/ACCESS.2017.2779475
|
| [36] |
J. E. Contreras-Reyes, Lerch distribution based on maximum nonsymmetric entropy principle: application to Conway's game of life cellular automaton, Chaos Solitons Fract., 151 (2021), 111272. https://doi.org/10.1016/j.chaos.2021.111272 doi: 10.1016/j.chaos.2021.111272
|
| [37] |
G. Boillat, T. Ruggeri, Moment equations in the kinetic theory of gases and wave velocities, Contin. Mech. Thermodyn., 9 (1997), 205–212. https://doi.org/10.1007/s001610050066 doi: 10.1007/s001610050066
|
| [38] | X. W. Chen, W. Dai, Maximum entropy principle for uncertain variables, Int. J. Fuzzy Syst., 13 (2011), 232–236. |
| [39] |
K. Yao, J. W. Gao, W. Dai, Sine entropy for uncertain variable, Internat. J. Uncertain. Fuzziness Knowledge Based Systems, 21 (2013), 743–753. https://doi.org/10.1142/S0218488513500359 doi: 10.1142/S0218488513500359
|
| [40] |
W. Dai, Quadratic entropy of uncertain variables, Soft Comput., 22 (2018), 5699–5706. https://doi.org/10.1007/s00500-017-2602-y doi: 10.1007/s00500-017-2602-y
|
| [41] |
K. Yao, H. Ke, Entropy operator for membership function of uncertain set, Appl. Math. Comput., 242 (2014), 898–906. https://doi.org/10.1016/j.amc.2014.06.081 doi: 10.1016/j.amc.2014.06.081
|
| [42] |
K. Yao, Sine entropy of uncertain set and its applications, Appl. Soft Comput., 22 (2014), 432–442. https://doi.org/10.1016/j.asoc.2014.04.023 doi: 10.1016/j.asoc.2014.04.023
|
| [43] |
X. S. Wang, M. H. Ha, Quadratic entropy of uncertain sets, Fuzzy Optim. Decis. Mak., 12 (2013), 99–109. https://doi.org/10.1007/s10700-012-9140-y doi: 10.1007/s10700-012-9140-y
|
| [44] |
R. Gao, D. A. Ralescu, Elliptic entropy of uncertain set and its applications, Int. J. Intell. Syst., 33 (2018), 836–857. https://doi.org/10.1002/int.21970 doi: 10.1002/int.21970
|
| [45] |
H. Zhao, H. Ahmadzade, M. GhasemiGol, Tsallis entropy of uncertain sets and its application to portfolio allocation, J. Ind. Manag. Optim., 20 (2024), 2885–2905. https://doi.org/10.3934/jimo.2024032 doi: 10.3934/jimo.2024032
|
| [46] |
X. Li, B. D. Liu, Maximum entropy principle for fuzzy variables, Internat. J. Uncertain. Fuzziness Knowledge Based Systems, 15 (2007), 43–52. https://doi.org/10.1142/S0218488507004595 doi: 10.1142/S0218488507004595
|
| [47] | B. D. Liu, Some research problems in uncertainty theory, J. Uncertain Syst., 3 (2009), 3–10. |
| [48] |
B. D. Liu, Membership functions and operational law of uncertain sets, Fuzzy Optim. Decis. Mak., 11 (2012), 387–410. https://doi.org/10.1007/s10700-012-9128-7 doi: 10.1007/s10700-012-9128-7
|
| [49] |
B. D. Liu, A new definition of independence of uncertain sets, Fuzzy Optim. Decis. Mak., 12 (2013), 451–461. https://doi.org/10.1007/s10700-013-9164-y doi: 10.1007/s10700-013-9164-y
|
| [50] | B. D. Liu, Uncertainty theory: A branch of mathematics for modeling human uncertainty, Berlin, Heidelberg: Springer, 2010. https://doi.org/10.1007/978-3-642-13959-8 |
| [51] |
X. F. Yang, J. W. Gao, Some results of moments of uncertain set, J. Intell. Fuzzy Syst., 28 (2015), 2433–2442. https://doi.org/10.3233/IFS-141523 doi: 10.3233/IFS-141523
|
| [52] | I. S. Gradshteyn, I. M. Ryzhik, Table of integrals, series, and products, Academic Press, 2014. https://doi.org/10.1016/C2010-0-64839-5 |
| [53] | I. M. Gelfand, R. A. Silverman, Calculus of variations, Courier Corporation, 2000. |