[1] B. Ahmad, A. Kharal, On fuzzy soft sets, Advances in Fuzzy Systems, 2009 (2009), 1-6.
[2] M. I. Ali, M. Shabir, Logic connectives for soft sets and fuzzy soft sets, IEEE Transactions on Fuzzy System, 22(6) (2014), 1431-1442.
[3] S. Das, S. Kar, Group decision making in medical system: An intuitionistic fuzzy soft set approach, Applied Soft Computing, 24 (2014), 196-211.
[4] S. Das, M. B. Kar, S. Kar, T. Pal, An approach for decision making using intuitionistic trapezoidal fuzzy soft set, Annals of Fuzzy Mathematics and Informatics, 16(1) (2018), 99-116.
[5] S. Das, M. B. Kar, T. Pal, S. Kar, Multiple attribute group decision making using interval-valued intuitionistic fuzzy soft matrix, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), (2014), 2222-2229.
[6] S. Das, D. Malakar, S. Kar, T. Pal, Correlation measure of hesitant fuzzy soft sets and their application in decision making, Neural Computing and Applications, 31 (2017), 1023-1039.
[7] D. Dubois, H. Prade, A note on measures of specificity for fuzzy sets, International Journal of General Systems, 10 (1985), 279-283.
[8] S. Enginoglu, N. Cagman, F. Citak, Fuzzy soft set theory and its application, International Journal of Fuzzy Systems, 8(3) (2011), 137-147.
[9] J. A. Goguen, L-fuzzy sets, Journal of Mathematical Analysis and Application, 18 (1967), 145-174.
[10] J. A. Goguen, The logic of inexact concepts, Synthese, 19 (1969), 325-373.
[11] E. Guner, H. Aygun, Spherical fuzzy soft sets: Theory and aggregation operator with its applications, Iranian Journal of Fuzzy Systems, 19(2) (2022), 83-97.
[12] P. K. Maji, R. Biswas, R. Roy, Fuzzy soft sets, Journal of Fuzzy Mathematics, 9 (2001), 589-602.
[13] P. K. Maji, R. Roy, A fuzzy set theoretic approach to decision making problems, Journal of Computational and Applied Mathematics, 203 (2007), 412-418.
[14] P. Majumdar, S. K. Samanta, Generalized fuzzy soft sets, Computers and Mathematics with Applications, 59 (2010), 1425-1432.
[15] W. K. Min, Similarity in soft set theory, Applied Mathematics Letter, 25 (2012), 310-314.
[16] D. Molodtsov, Soft set theory-first results, Computers and Mathematics with Applications, 37 (1999), 19-31.
[17] B. Mondal, S. Raha, Approximate reasoning in management of hypertension, Facets of Uncertainties and Applications, 125 (2015), 225-233.
[18] E. S. Palmeira, B. C. Bedergal, Extension of fuzzy logic operators defined on bounded lattices via retractions, Computers and Mathematics with Application, 63 (2012), 1026-1038.
[19] Z. Pei, K. Qin, D. Meng, Y. Xu, A medical diagnostic support system for the management of hypertension (MED DIAG), Journal of Scientific Multidisiplinary Research, 3 (2011), 16-30.
[20] K. Rezaei, H. Rezaei, New distance and similarity measures for hesitant fuzzy soft sets, 16 (2019), 159-176.
[21] M. Shabir, M. I. Ali, M. Naz, Algebraic structures of soft sets associated with new operations, Computers and Mathematics with Application, 61 (2011), 2647-2654.
[22] R. R. Yager, Measuring tranquility and anxiety in decision making: An application of fuzzy sets, International Journal of General Systems, 8 (1982), 139-146.
[23] L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.
[24] M. A. Zehrui, W. Wangming, Logical operators on complete lattices, Information Sciences, 55 (1991), 77-97.