References:
[1] Zadeh, L. A. Fuzzy sets", In Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A Zadeh, pp. 394-432 (1996).
[2] Atanassov, K. T. Intuitionistic fuzzy sets", Fuzzy Sets and Systems, 20, pp. 87{96 (1986).
[3] Yager, R. R. Pythagorean fuzzy subsets", In 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), pp. 57-61 (2013).
[4] Smarandache, F. A unifying field of logics Neutrosophy: Neutrosophic probability, set and logic", American Research Press, Rehoboth (1998).
[5] Yager, R. R. Generalized orthopair fuzzy sets", IEEE Transactions on Fuzzy Systems, 25(5), pp. 1222- 1230 (2016).
[6] Ashraf, S., Abdullah, S., Mahmood,T., Ghani, F. and Mahmood, T. Spherical fuzzy sets and their applications in multi-attribute decision making problems", Journal of Intelligent and Fuzzy Systems, 36(3), pp. 2829-2844 (2019).
[7] Gundogdu, K. and Kahraman, C. Spherical fuzzy sets and spherical fuzzy TOPSIS method", Journal of Intelligent and Fuzzy Systems, 36(1), pp. 337-352 (2019).
[8] Abdullah, L. and Najib, L. A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process", Expert Systems with Applications, 41(7), pp. 3297-3305 (2014).
[9] Khatibi, V. and Montazer, G. A. Intuitionistic fuzzy set vs. fuzzy set application in medical pattern recognition", Artificial Intelligence in Medicine, 47(1), pp. 43-52 (2009).
[10] Kumar, K. and Garg, H. TOPSIS method based on the connection number of set pair analysis under interval-valued intuitionistic fuzzy set environment", Computational and Applied Mathematics, 37(2), pp. 1319-1329 (2018).
[11] Mabrouk, N. Green supplier selection using fuzzy Delphi method for developing sustainable supply chain", Decision Science Letters, 10(1), pp. 63-70 (2021).
[12] Marzouk, M. and Abdelakder, E. On the use of multi-criteria decision making methods for minimizing environmental emissions in construction projects", Decision Science Letters, 8(4), pp. 373-392 (2019).
[13] Olgun, M., Turkarslan, E., Unver, M. and Ye, J. A cosine similarity measure based on the Choquet integral for intuitionistic fuzzy sets and ts applications to pattern recognition", Informatica, 32(4), pp.849-864 (2021).
[14] Ozcelik, G. and Nalkiran, M. An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system", International Journal of Fuzzy Systems, 23, pp.2348 -2366, (2021).
[15] Oztaysi, B., Onar, S. C., Kahraman, C., and Yavuz, M. Multi-criteria alternative-fuel technology selection using interval-valued intuitionistic fuzzy sets", Transportation Research Part D: Transport and Environment, 53, pp. 128-148 (2017).
[16] Riaz, M., Naeem, K. and Afzal, D. Pythagorean m-polar fuzzy soft sets with TOPSIS method for MCGDM", Punjab University Journal of Mathematics, 52(3), pp. 21-46 (2020).
[17] Turkarslan, E., Ye, J., Unver, M. and Olgun, M. Consistency fuzzy sets and a cosine similarity measure in fuzzy multiset setting and application to medical diagnosis", Mathematical Problems in Engineering,Volume 2021, Article ID 9975983, (2021), doi: https://doi.org/10.1155/2021/9975983.
[18] Yeni, F. B. and Ozcelik, G. Interval-valued Atanassov intuitionistic Fuzzy CODAS method for multi criteria group decision making problems", Group Decision and Negotiation, 28(2), pp. 433-452 (2019).
[19] Wang, H., Smarandache, F., Zhang, Y. Q. and Sunderraman, R. Single valued neutrosophic sets",Multispace Multistruct, 4, pp. 410{413, (2010).
[20] Wang, H., Smarandache, F., Zhang, Y. Q. and Sunderraman, R. Interval neutrosophic sets and logic",Theory and Applications in Computing, Hexis, Phoenix, (2005).
[21] Jun, Y. B., Smarandache, F. and Kim, C.S. Neutrosophic cubic sets", New Math. Nat. Comput., 13(1),pp. 41{54 (2017).
[22] Ye, J. An extended TOPSIS method for multiple attribute group decision making based on single valued neutrosophic linguistic numbers", Journal of Intelligent and Fuzzy Systems, 28(1), pp. 247{255 (2015).
[23] Ye, J. A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets", Journal of Intelligent and Fuzzy Systems, 26(5), pp. 2459-2466 (2014).
[24] Unver, M., Turkarslan, E., Ozcelik, N., Olgun, M. and Ye, J. Intuitionistic fuzzy-valued neutrosophic multi-sets and numerical applications to classification", Complex Intelligent Systems, (2022),https://doi.org/10.1007/s40747-021-00621-5.
[25] Shannon C.E. A Mathematical Theory of Communication", The Bell System Technical Journal, 27, pp.379-423 (1948).
[26] Zadeh, L. A. Probability measures of fuzzy events", Journal of Mathematical Analysis and Application, 23, pp. 421-427 (1968).
[27] De Luca, A. and S. Termini. A definition of nonprobabilistic entropy in the setting of fuzzy sets theory", Information and Control, 20, pp. 301-312 (1972).
[28] Yager, R. R. On the measure of fuzziness and negation, Part I: Membership in the Unit Interval". International Journal of General Systems, 5, 221-229 (1979).
[29] Ye, J. Two effective measures of intuitionistic fuzzy entropy", Computing, 87, pp. 55{62 (2010).
[30] Ye, J. Multicriteria fuzzy decision-making method using entropy weights-based correlation coefficients of interval-valued intuitionistic fuzzy sets", Applied Mathematical Modelling, 34, pp. 3864{3870 (2010).
[31] Zhang, Q. S., Xing, H. Y., Liu, F. C., Ye, J. and Tang, P. Some new entropy measures for intervalvalued intuitionistic fuzzy sets based on distances and their relationships with similarity and inclusion measures", Information Sciences, 283, pp. 55{69 (2014).
[32] Cui, W. and Ye, J. Generalized distance-based entropy and dimension root entropy for simplified neutrosophic sets", Entropy, 20(11) (2018).
[33] Ye, J., Cui, W. Exponential entropy for simplified neutrosophic sets and its application in decision making", Entropy, 20(5), pp. 357 (2018).
[34] Cui, W. and Ye, J. Improved symmetry measures of simpli ed neutrosophic sets and their decisionmaking method based on a sine entropy weight model", Symmetry, 10(6), pp. 225-236 (2018).
[35] Xiao, F. A distance measure for intuitionistic fuzzy sets and its application to pattern classification problems", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(6), pp. 3980-3992 (2019).
[36] Kullback, S. and Leibler, R. A. "On information and sufficiency", The annals of mathematical statistics, 22(1), pp. 79-86 (1951).
[37] Opricovic, S. "Multicriteria optimization of civil engineering systems", Fac. Civ. Q8 Eng. Belgrade, 2, pp. 5{21 (1998).
[38] Parhizgarsharif, A., Lork, A., and Telvari, A. A hybrid approach based on the BWM-VIKOR and GRA for ranking facility location in construction site layout for Mehr project in Tehran", Decision Science Letters, 8(3), pp. 233-248 (2019).
[39] Lin, M., Chen, Z., Xu, Z., Gou, X. and Herrera, F. "Score function based on concentration degree for probabilistic linguistic term sets: an application to TOPSIS and VIKOR", Information Sciences, 551,pp. 270-290 (2021).
[40] Opricovic, S. Fuzzy VIKOR with an application to water resources planning", Expert Systems with Applications, 38, pp. 12983{12990 (2011).
[41] Luo, X. and Wang, X. Extended VIKOR method for intuitionistic fuzzy multiattribute decision-making based on a new distance measure", Mathematical Problems in Engineering, Article ID 4072486, (2017).
[42] Wu, L., Gao, H. and Wei, C. VIKOR method for nancing risk assessment of rural tourism projects under interval-valued intuitionistic fuzzy environment", Journal of Intelligent and Fuzzy Systems, 37, pp.2001-2008 (2019).
[43] Liao, H. C. and Xu, Z.S. A VIKOR-based method for hesitant fuzzy multi-criteria decision-making",Fuzzy Optimization and Decision Making, 12(4), pp. 373{392 (2013).
[44] Dong, J. Y., Yuan, F. F. and Wan, S. P. Extended VIKOR method for multiple criteria decision-making with linguistic hesitant fuzzy information", Computers Industrial Engineering, 112, pp. 305-319 (2017).
[45] Kutlu G. F. and Kahraman, C. A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection", Journal of Intelligent and Fuzzy Systems, 37, pp. 1197{1211 (2019).
[46] Mahmood, T. and Ali, Z. Aggregation operators and VIKOR method based on complex q-rung orthopair uncertain linguistic informations and their applications in multi-attribute decision making", Computational and Applied Mathematics, 39, pp. 306 (2020).
[47] Zare, A., Feylizadeh, M., Mahmoudi, A., and Liu, S. Suitable computerized maintenance management system selection using grey group TOPSIS and fuzzy group VIKOR: a case study", Decision Science Letters, 7(4), pp. 341-358 (2018).
[48] Fei, L., Deng, Y. and Hu, Y. "DS-VIKOR: A new multi-criteria decision-making method for supplier selection", International Journal of Fuzzy System, 21(1), pp. 157{175 (2019).
[49] Mohsen, O. and Fereshteh, N. An extended VIKOR method based on entropy measure for the failuremodes risk assessment A case study of the geothermal power plant(GPP)", Safety Science, 92, pp.160-172 (2017).
[50] Rani, P., Mishra, A. R., Pardasani, K. R., Mardani, A., Liao, H. and Streimikiene, D. A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India", Journal of Cleaner Production, 238, pp. 117936 (2019).
[51] Nancy and Garg, H. "An improved score function for ranking neutrosophic sets and its application to decision-making process", International Journal for Uncertainty Quantification, 6(5), pp.377 - 385 (2016).
[52] Borda, J. C. Memoire sur les elections au scrutin", Historie de Academie Royaledes Sciences, Paris (1784).
[53] Wang, L. and Garg, H. Algorithm for multiple attribute decision-making with interactive Archimedean norm operations under Pythagorean fuzzy uncertainty", International Journal of Compututational Intelligence Systems, 14(1), pp. 503-527 (2021).