FUZZY RISK ANALYSIS BASED ON A NEW METHOD FOR RANKING GENERALIZED FUZZY NUMBERS

[1] B. S. Ahn, Compatible weighting method with rank order centroid: Maximum entropy ordered
weighted averaging approach, Eur. J. Oper. Res., 212(3) (2011), 552–559.
[2] E. Akyar, H. Akyar and S. A. D¨uzce, Fuzzy risk analysis based on a geometric ranking method
for generalized trapezoidal fuzzy numbers, J. Intell. Fuzzy Syst., 25(1) (2013), 209–217.
[3] L. Aliahmadipour and E. Eslami, GHFHC: Generalized hesitant fuzzy hierarchical clustering
algorithm, Int. J. Intell. Syst., 31(9) (2016), 855–871.
[4] I. M. Aliev and Z. Kara, Fuzzy system reliability analysis using time dependent fuzzy set,
Control Cybern., 33(4) (2004), 653–662.
[5] S. Aytar, Order intervals in the metric space of fuzzy numbers, Iranian Journal of Fuzzy
Systems, 12(5) (2015), 139–147.
[6] A. S. A. Bakar and A. Gegov, Ranking of fuzzy numbers based on centroid point and spread,
J. Intell. Fuzzy Syst., 27(3) (2014), 1179–1186.
[7] S. J. Chen and S. M. Chen, Fuzzy risk analysis based on the ranking of generalized trapezoidal
fuzzy numbers, Appl. Intell., 26(1) (2007), 1–11.
[8] S. M. Chen and J. H. Chen, Fuzzy risk analysis based on ranking generalized fuzzy numbers
with different heights and different spreads, Expert. Syst. Appl., 36(3) (2009), 6833–6842.
[9] S. M. Chen, A. Munif, G. S. Chen, H. C. Liu and B. C. Kuo, Fuzzy risk analysis based on
ranking generalized fuzzy numbers with different left heights and right heights, Expert Syst.
Appl., 39(7) (2012), 6320 – 6334.

[10] S. M. Chen and K. Sanguansat, Analyzing fuzzy risk based on a new fuzzy ranking method
between generalized fuzzy numbers, Expert Syst. Appl., 38 (2011), 2163 – 2171.
[11] C. C. Chou, A generalized similarity measure for fuzzy numbers, J. Intell. Fuzzy Syst., 30(2)
(2016), 1147–1155.
[12] T. C. Chu and C. T. Tsao, Ranking fuzzy numbers with an area between the centroid point
and original point, Comput. Math. Appl., 43 (2002), 111–117.
[13] X. Deng, D. Han, J. Dezert, Y. Deng and Y. Shyr, Evidence combination from an evolutionary
game theory perspective, IEEE T. Cybernetics, 46(9) (2016), 2070–2082.
[14] X. Deng, W. Jiang and J. Zhang, Zero-sum matrix game with payoffs of Dempster-
Shafer belief structures and its applications on sensors, Sensors, Article ID 922,
DOI:10.3390/s17040922, 17(4) (2017), 1-22.
[15] X. Deng, F. Xiao and Y. Deng, An improved distance-based total uncertainty measure in
belief function theory, Appl. Intell., 46(4) (2017), 898–915.
[16] Y. Deng, Deng entropy, Chaos Soliton. Fract., 91 (2016), 549–553.
[17] D. S. Dinagar and A. Anbalagan, A new similarity measure between type-2 fuzzy numbers
and fuzzy risk analysis, Iranian Journal of Fuzzy Systems, 10(5) (2013), 79–95.
[18] A. Ebrahimnejad and J. L. Verdegay, An efficient computational approach for solving type-2
intuitionistic fuzzy numbers based transportation problems, Int. J. Comput. Int. Sys., 9(6)
(2016), 1154–1173.
[19] Y. B. Gong, L. L. Dai and N. Hu, Multi-attribute decision making method based on Bonferroni
mean operator and possibility degree of interval type-2 tarpezoidal fuzzy sets, Iranian Journal
of Fuzzy Systems, 13(5) (2016), 97–115.
[20] T. Hajjari, Fuzzy risk analysis based on ranking of fuzzy numbers via new magnitude method,
Iranian Journal of Fuzzy Systems, 12(3) (2015), 17–29.
[21] W. Jiang, S. Wang, X. Liu, H. Zheng and B. Wei, Evidence conflict measure based on owa
operator in open world, PloS one, 12(5) (2017), 1–18, e0177,828.
[22] W. Jiang, B. Wei, Y. Tang and D. Zhou, Ordered visibility graph average aggregation
operator: An application in produced water management, Chaos, Article ID 023,117,
DOI:10.1063/1.4977186, 27(2) (2017), 1-10.
[23] W. Jiang, B. Wei, J. Zhan, C. Xie and D. Zhou, A visibility graph power averaging
aggregation operator: A methodology based on network analysis, Comput. Ind. Eng.,
DOI:10.1016/j.cie.2016.09.009, 101 (2016), 260–268.
[24] W. Jiang and S.Wang, An uncertainty measure for interval-valued evidences, Int. J. Comput.
Commun., 12(5) (2017), 631–644.
[25] W. Jiang, C. Xie, M. Zhuang, Y. Shou and Y. Tang, Sensor data fusion with Z-numbers and
its application in fault diagnosis, Sensors, Article ID 1509, DOI:10.3390/s16091509, 16(9)
(2016), 1–22.
[26] W. Jiang, C. Xie, M. Zhuang and Y. Tang, Failure mode and effects analysis
based on a novel fuzzy evidential method, Appl.Soft Comput., DOI:
http://dx.doi.org/doi:10.1016/j.asoc.2017.04.008, 57 (2017), 672–683,
[27] W. Jiang and J. Zhan, A modified combination rule in generalized evidence theory, Appl.
Intell., DOI:10.1007/s10489-016-0851-6, 46(3) (2017), 630–640.
[28] B. Kang, Y. Hu, Y. Deng and D. Zhou, A New Methodology of Multicriteria Decision-Making
in Supplier Selection Based on Z-Numbers, Math. Probl. Eng., DOI:10.1155/2016/8475987,
2016(1) (2016), 1-17.
[29] J. Kerr-Wilson and W. Pedrycz, Some new qualitative insights into quality of fuzzy rule-based
models, Fuzzy Set. Syst., 307 (2017), 29–49.
[30] L. Kovarova and R. Viertl, The generation of fuzzy sets and the construction of characterizing
functions of fuzzy data, Iranian Journal of Fuzzy Systems, 12(6) (2015), 1–16.
[31] K. U. Madhuri, S. S. Babu and N. R. Shankar, Fuzzy risk analysis based on the novel fuzzy
ranking with new arithmetic operations of linguistic fuzzy numbers, J. Intell. Fuzzy Syst.,
26(5) (2014), 2391–2401.
[32] A. M. Nejad and M. Mashinchi, Ranking fuzzy numbers based on the areas on the left and
the right sides of fuzzy number, Comput. Math. Appl., 61(2) (2011), 431–442.

[33] M. T. Nouei, A. V. Kamyad, M. R. Sarzaeem and S. Ghazalbash, Fuzzy risk assessment of
mortality after coronary surgery using combination of adaptive neuro-fuzzy inference system
and K-means clustering, Expert Syst., 33(3) (2016), 230–238.
[34] M. O’Hagan, Aggregating template or rule antecedents in real-time expert systems with fuzzy
set logic, In: in proc. 22nd Annu. IEEE Asilomar Conf. Signals, Systems, Computers, Pacific
Grove, CA, 2(2) (1988), 681–689.
[35] G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, 20(1) (1976),
106-106.
[36] M. Shamsizadeh and M. M. Zahedi, Intuitionistic general fuzzy automata, Soft Comput.,
20(9) (2016), 3505–3519.
[37] G. P. Silveira and L. C. D. Barros, Analysis of the dengue risk by means of a Takagi-Sugenostyle
model, Fuzzy Set. Syst., 277(C) (2015), 122–137.
[38] E. B. Smith and R. Langari, Fuzzy multiobjective decision making for navigation of mobile
robots in dynamic, unstructured environments, J. Intell. Fuzzy Syst., 14(2) (2003), 95–108.
[39] J. Wang, Y. Hu, F. Xiao, X. Deng and Y. Deng, A novel method to use fuzzy soft sets in
decision making based on ambiguity measure and Dempster-Shafer theory of evidence: An
application in medical diagnosis, Artif. Intell. Med., 69 (2016), 1–11.
[40] Y. J. Wang, Ranking triangle and trapezoidal fuzzy numbers based on the relative preference
relation, Appl. Math. Model., 39(2) (2014), 586–599.
[41] Y. M. Wang, J. B. Yang, D. L. Xu and K. S. Chin, On the centroids of fuzzy numbers, Fuzzy
Set. Syst., 157(7) (2006), 919–926.
[42] S. H.Wei and S. M. Chen, Fuzzy risk analysis based on interval-valued fuzzy numbers, Expert.
Syst. Appl., 36(2) (2009), 2285–2299.
[43] D. Wu, X. Liu, F. Xue, H. Zheng, Y. Shou and W. Jiang, A new medical diagnosis method
based on Z-numbers, Appl. Intell., DOI:10.1007/s10489-017-1002-4, 2017(1) (2017), 1–14.
[44] R. R. Yager, Ranking fuzzy subsets over the unit interval, IEEE Conference on Decision and
Control including the 17th Symposium on Adaptive Processes, (1978), 1435–1437.
[45] R. R. Yager, On ordered weighted averaging aggregation operators in multicriteria decisionmaking,
IEEE T. Syst. Man. CY-S., 18(1) (1988), 183–190.
[46] V. F. Yu, H. T. X. Chi, L. Q. Dat, P. N. K. Phuc and C. W. Shen, Ranking generalized fuzzy
numbers in fuzzy decision making based on the left and right transfer coefficients and areas,
Appl. Math. Model., 37(16-17) (2013), 8106–8117.
[47] L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338–353.
[48] L. A. Zadeh, A note on Z-numbers, Inform. Sciences, 181(14) (2011), 2923–2932.
[49] R. Zhang, X. Ran, C. Wang and Y. Deng, Fuzzy evaluation of network vulnerability, Qual.
Reliab. Eng. Int., 32(5) (2016), 1715–1730.
[50] X. Zhang, Y. Deng, F. T. S. Chan, A. Adamatzky and S. Mahadevan, Supplier selection
based on evidence theory and analytic network process, P. I. Mech. Eng. B-J. Eng., 230(3)
(2016), 562–573