[1] Atanassov, K. (1986) Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87-96.
[2] Sahil, M., A., & Lohani, D. (2024) Comprehensive intuitionistic fuzzy network data envelopment analysis incorporating undesirable outputs and shared resources, Methods X,, 12, https://doi.org/10.1016/j.mex.2024.102710.
[3] Pawlak, Z. (1982) Rough sets. International Journal of Parallel Programming, Vol. 11, pp. 341-356.
[4] Liu, B.D. (2004) Uncertain Theory: An Introduction to its Axiomatic Foundation. Springer, Berlin.
[5] Khanjani, R., Charles, V., and Jalalzadeh, L, (2014) Fuzzy rough DEA model: A possibility and expected value approaches. Expert Systems with Applications, 41, 434-444.
[6] Jafarzadeh, M., Davvaz, B. (2013) Rough Intuitionistic Fuzzy Information Systems. Fuzzy Information and Engineering, 5:4, 445-458.
[7] Rizvi, R., Naqvi, H. J., Nadeem, D., (2002) Rough Intuitionistic Fuzzy Sets. Conference: Proceedings of the 6th Joint Conference on Information Science.
[8] Kumar, A. T., Nath, A., Kumar, R. P., Maratha, P., (2024) A novel intuitionistic fuzzy rough instance selection and attribute reduction with kernelized intuitionistic fuzzy C-means clustering to handle imbalanced datasets. Expert Systems with Applications, 251, 437 -449.
[9] Jain, P., Tiwari, A. & Som, T. (2024) Intuitionistic fuzzy rough set model based on k-means and its application to enhance prediction of aptamer-protein interacting pairs. J Ambient Intell Human Comput, 15, 3575-3586.
[10] Noorjahan S., Sharief Basha S. (2024) Developing an intuitionistic fuzzy rough new correlation coefficient approach for enhancing robotic vacuum cleaner. Science Progress. 107(3).
[11] Burillo, P. Bustince, H. (1996) Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets, Fuzzy Sets and Systems, 78(3), 305 - 316.
[12] Grzegorzewski, p., (2002) Intuitionistic fuzzy numbers. Accepted for the precedingof the IFSA, 2003, world Congress.
[13] Zadeh, L. A. (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 9-34.
