[1] Abbasabandy, S. and Alavi, M. A method for solving fuzzy linear systems, Iran. J. Fuzzy Syst. 2(2) (2005) 37–43.
[2] Abbasbandy, S. and Amirfakhrian, M. The nearest trapezoidal form of a generalized left right fuzzy number, Internat. J. Approx. Reason. 43(2) (2006) 166–178.
[3] Abbasbandy, S.and Asady, B. A note on ‘‘A new approach for defuzzifi-cation’’[Fuzzy Sets and Systems 111 (2000), no. 3, 351–356; 1 748 552] by M. Ma, A. Kandel and M. Friedman, Fuzzy Sets Syst. 128 (2002) 131–132.
[4] Abbasbandy, S. and Asady, B. The nearest trapezoidal fuzzy number to a fuzzy quantity, Appl. Math. Comput. 156 (2004) 381–386.
[5] Abbasbandy, S. and Hajjari, T. Weighted trapezoidal approximation-preserving cores of a fuzzy number, Comput. Math. Appl. 59(9) (2010) 3066–3077.
[6] Amirfakhrian, M. A New Parametric Distance and Using it to Find The Nearest Approximation of A Fuzzy Number, Conference: 11th Iranian Conference of Fuzzy Systems, 2011.
[7] M. Amirfakhrian and S. Bagherian, The nearest approximation of a fuzzy number by a new parametric distance, Conference: 40th Annual Iranian Mathematics Conference, 2009.
[8] Ban, A.I and Coroianu, L. Nearest interval, triangular and trapezoidal approximation of a fuzzy number preserving ambiguity, Internat. J. Ap-prox. Reason. 53 (5) (2012) 805–836.
[9] Coroianu, L. Trapezoidal approximations of fuzzy numbers using quadratic programs,Fuzzy Sets Syst. 417 (2021) 71–92.
[10] Coroianu, L., Gagolewski, M. and Grzegorzewski, P. Piecewise linear approximation of fuzzy numbers: algorithms, arithmetic operations and stability of characteristics, Soft Comput. 23 (2019) 9491–9505.
[11] Dubois, D. and Prade, H. Fuzzy number: an overview, Fuzzy number: an overview,
[12] T. Hajjari, Approximation of fuzzy numbers via 0.5-Level and Mean core, Int. J. Appl. Math. Stat. (22) (2011) 69–78.
[13] T. Hajjari and H. Mahzoon, Approximation of a fuzzy number by two main characteristics, Mathematical Inverse Problems, 1(1) (2014) 101–111.
[14] Ghanbari, M., Allahviranloo, T., Nuraei, R. and Pedrycz, W. A new effective approximate multiplication operation on LR fuzzy numbers and its application, Soft Comput. 26(9)(2022) 4103–4113.
[15] Giachetti, R.E. and Young, R.E. A parametric representation of fuzzy numbers and their arithmetic operators, Fuzzy Sets Syst. 91 (2) (1997)185–202.
[16] Guerra, M.L. and Stefanini, L.Approximate fuzzy arithmetic operations using monotonic interpolations, Fuzzy Sets Syst. 150 (2005) 5–33.
[17] Klir, G.J., St. Clair, U. and Yuan, B., Fuzzy set theory: foundations and applications, Prentice-Hall Inc. 1997.
[18] Ma, M., Kandel, A. and Friedman, M. Correction to a new approach for the difizification, “[Fuzzy Sets and Systems 111 (2000) 351-356].” Fuzzy Sets Syst. 128 (1) (2002) 133–134.
[19] Zheng, Q. and Zhang, L. Global minimization of constrained problems with discontinuous penalty functions, Global optimization, control, and games, III, Comput. Math. Appl. 37 (1999), no. 4-5, 41–58.
[20] Voxman, W. Canonical representation of discrete fuzzy numbers, Fuzzy Set Syst. 118 (3) (2001) 557–466.
[21] Yeh, C.-T. Existence of interval, triangular, and trapezoidal approxima-tions of fuzzy numbers under a general condition, Fuzzy Sets Syst. 310 (2017) 1–13.
[22] Zadeh, L.A. The concept of a linguistic variable and its application to approximate reasoning-I, Inf. Sci. 8 (1975) 199–249.
[23] Zadeh L.A. The concept of a linguistic variable and its application to approximate reasoning-II, Inf. Sci. 8 (1975) , 301–357.
[24] Zadeh L.A. The concept of a linguistic variable and its application to approximate reasoning-III, Inf. Sci. 9 (1975) 43–80.
[25] Zhou, J., Yang, F. and Wang, K. Fuzzy arithmetic on LR fuzzy numbers with applications to fuzzy programming, J. Intell. Fuzzy Syst. 30 (2016) 71–87.
