[1] Ahmed, J. (2021). LR-type fully single-valued neutrosophic linear programming problems. Neutrosophic Sets and Systems, 46(1), 416-444.
[2] Atanassov, K. T. (2012). On intuitionistic fuzzy sets theory (Vol. 283). Springer.
[3] Abdul-Wahab, S. A., Bakheit, C. S., & Al-Alawi, S. M. (2005). Principal component and multi- pleregression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environmental Modelling & Software, 20(10), 1263-1271.
[4] Bajestani, N. S., Kamyad, A. V., & Zare, A. (2017). A piecewise type-2 fuzzy regression model. International Journal of Computational Intelligence Systems, 10(1), 734-744.
[5] Behdani, Z. The Least Squares Method for Estimating Regression Model Parameters with Bipolar Fuzzy Numbers. Available at SSRN 4717871.
[6] Boukezzoula, R., & Coquin, D. (2021). Interval-valued fuzzy regression: Philosophical and method- ological issues. Applied Soft Computing, 103, 107145.
[7] Cervig6n, R., Moreno, J., Reilly, R. B., Perez-Villacastin, J., & Castells, F. (2012). Quantification of anaesthetic effects on atrial fibrillation rate by partial least-squares. Physiological Measurement, 33(10), 1757.
[8] Chachi, J., Akhoond, M. R., & Handali, K. (2023). Statistical inference of fuzzy weighted regression based on bootstrap approach. Fuzzy Systems and its Applications.
[9] Chen, L. H., & Nien, S. H. (2020). Approach for establishing intuitionistic fuzzy linear regression models based on weakest t-norm arithmetic. IEEE Transactions on Fuzzy Systems, 29(6), 1431-1445.
[10] Chen, L. H., & Hsueh, C. C. (2009). Fuzzy regression models using the least-squares method based on the concept of distance. IEEE Transactions on Fuzzy Systems, 17(6), 1259-1272.
[11] Darehmiraki, M. (2020). A solution for the neutrosophic linear programming problem with a new ranking function. In Optimization theory based on Neutrosophic and Plithogenic Sets (pp. 235-259). Academic Press.
[12] Diamond, P. (1988). Fuzzy least squares. Information sciences, 46(3), 141-157.
[13] Hose, D., & Hanss, M. (2019). Fuzzy linear least squares for the identification of possibilistic re- gression models. Fuzzy Sets and Systems, 367, 82-95.
[14] Hesamian, G., Torkian, F., Johannssen, A., & Chukhrova, N. (2024). A fuzzy nonparametric regres- sion model based on an extended center and range method. Journal of Computational and Applied Mathematics, 436, 115377.
[15] Jiang, L., & Liao, H. (2020). Mixed fuzzy least absolute regression analysis with quantitative and probabilistic linguistic information. Fuzzy Sets and Systems, 387, 35-48.
[16] Kong, L. (2022). Fuzzy linear regression model based on adaptive lasso method. International Jour- nal of Fuzzy Systems, 24(1), 508-518.
[17] Karamacoska, D., Barry, R. J., & Steiner, G. Z. (2019). Using principal components analysis to examine resting state EEG in relation to task performance. Psychophysiology, 56(5), e13327.
[18] Khammar, A. H., Arefi, M., & Akbari, M. G. (2020). A robust least squares fuzzy regression model based on kernel function. Iranian Journal of Fuzzy Systems, 17(4), 105-119.
[19] Kumar, S., & Chong, I. (2018). Correlation analysis to identify the effective data in machine learning: Prediction of depressive disorder and emotion states. International journal of environmental research and public health, 15(12), 2907.
[20] Nagarajan, D., Broumi, S., Smarandache, F., & Kavikumar, J. (2021). Analysis of neutrosophic multiple regression. Neutrosophic Sets and Systems, 43, 44-53.
[21] Parvathi, R., Malathi, C., Akram, M., & Atanassov, K. T. (2013). Intuitionistic fuzzy linear regres- sion analysis. Fuzzy Optimization and Decision Making, 12, 215-229.
[22] Smarandache, F. (2014). Introduction to neutrosophic statistics. Infinite Study.
[23] Tanaka, H., & Watada, J. (1988). Possibilistic linear systems and their application to the linear re- gression model. Fuzzy sets and systems, 27(3), 275-289.
[24] Tanaka, H., & Lee, H. (1998). Interval regression analysis by quadratic programming approach. IEEE Transactions on Fuzzy Systems, 6(4), 473-481.
[25] Wang, H., Smarandache, F., Zhang, Y., & Sunderraman, R. (2010). Single valued neutrosophic sets. Infinite study, 12.
[26] Zadeh, L. A. (1979). Fuzzy sets and information granularity. Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers, 433-448.