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@article{IJAMCS_2021_31_3_a3, author = {Xia, Sisi and Yang, Haoran and Chen, Lin}, title = {An incomplete soft set and its application in {MCDM} problems with redundant and incomplete information}, journal = {International Journal of Applied Mathematics and Computer Science}, pages = {417--430}, publisher = {mathdoc}, volume = {31}, number = {3}, year = {2021}, language = {en}, url = {http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a3/} }
TY - JOUR AU - Xia, Sisi AU - Yang, Haoran AU - Chen, Lin TI - An incomplete soft set and its application in MCDM problems with redundant and incomplete information JO - International Journal of Applied Mathematics and Computer Science PY - 2021 SP - 417 EP - 430 VL - 31 IS - 3 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a3/ LA - en ID - IJAMCS_2021_31_3_a3 ER -
%0 Journal Article %A Xia, Sisi %A Yang, Haoran %A Chen, Lin %T An incomplete soft set and its application in MCDM problems with redundant and incomplete information %J International Journal of Applied Mathematics and Computer Science %D 2021 %P 417-430 %V 31 %N 3 %I mathdoc %U http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a3/ %G en %F IJAMCS_2021_31_3_a3
Xia, Sisi; Yang, Haoran; Chen, Lin. An incomplete soft set and its application in MCDM problems with redundant and incomplete information. International Journal of Applied Mathematics and Computer Science, Tome 31 (2021) no. 3, pp. 417-430. http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a3/
[1] [1] Akram, M., Shumaiza and Arshad, M. (2020). Bipolar fuzzy TOPSIS and bipolar fuzzy ELECTRE-I methods to diagnosis, Computational and Applied Mathematics 39(1), Article no. 7.
[2] [2] Alkhazaleh, S. and Salleh, A.R. (2012). Generalised interval-valued fuzzy soft set, Journal of Applied Mathematics 2012, Article no. 870504.
[3] [3] Chen, D.G., Tsang, E.C.C., Yeung, D.S. and Wang, X.Z. (2005). The parameterization reduction of soft sets and its applications, Computers and Mathematics with Applications 49(5–6): 757–763.
[4] [4] Das, S., Kar, M.B., Kar, S. and Pal, T. (2018). An approach for decision making using intuitionistic trapezoidal fuzzy soft set, Annals of Fuzzy Mathematics and Informatics 16(1): 99–116.
[5] [5] Deng, T. and Wang, X. (2013). An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets, Applied Mathematical Modelling 37(6): 4139–4146.
[6] [6] Garg, H. and Arora, R. (2018). Bonferroni mean aggregation operators under intuitionistic fuzzy soft set environment and their applications to decision-making, Journal of the Operational Research Society 69(11): 1711–1724.
[7] [7] Gau, W.L. and Buehrer, D.J. (1993). Vague sets, IEEE Transactions on Systems Man and Cybernetics 23(2): 610–614.
[8] [8] Goguen, J.A. (1967). L-fuzzy sets, Journal of Mathematical Analysis and Applications 18(1): 145–174.
[9] [9] Gong, K.,Wang, P. and Peng, Y. (2017). Fault-tolerant enhanced bijective soft set with applications, Applied Soft Computing 54: 431–439.
[10] [10] Gong, K., Xiao, Z. and Zhang, X. (2010). The bijective soft set with its operations, Computers and Mathematics with Applications 60(8): 2270–2278.
[11] [11] Hong, D.H. and Choi, C.H. (2000). Multicriteria fuzzy decision-making problems based on vague set theory, Fuzzy Sets and Systems 114(1): 103–113.
[12] [12] Inbarani, H.H., Kumar, S.U., Azar, A.T. and Hassanien, A.E. (2018). Hybrid rough-bijective soft set classification system, Neural Computing and Applications 29(8): 67–78.
[13] [13] Jiang, Y., Tang, Y., Chen, Q., Liu, H. and Tang, J. (2010). Interval-valued intuitionistic fuzzy soft sets and their properties, Computers and Mathematics with Applications 60(3): 906–918.
[14] [14] Khan, A. and Zhu, Y. (2020). New algorithms for parameter reduction of intuitionistic fuzzy soft sets, Computational and Applied Mathematics 39(3), Aricle no. 232.
[15] [15] Kong, Z., Gao, L.Q., Wang, L.F. and Li, S. (2008). The normal parameter reduction of soft sets and its algorithm, Computers and Mathematics with Applications 56(12): 3029–3037.
[16] [16] Kryszkiewicz, M. (1999). Rules in incomplete information systems, Information Sciences 113(3–4): 271–292.
[17] [17] Li, M.-Y., Fan, Z.-P. and You, T.-H. (2018). Screening alternatives considering different evaluation index sets: A method based on soft set theory, Applied Soft Computing 64: 614–626.
[18] [18] Li, Z., Wen, G. and Xie, N. (2015). An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis, Artificial Intelligence in Medicine 64(3): 161–71.
[19] [19] Liu, Y., Qin, K., Rao, C. and Mahamadu Alhaji, M. (2017). Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set, International Journal of Applied Mathematics and Computer Science 27(1): 157–167, DOI: 10.1515/amcs-2017-0011.
[20] [20] Maji, P.K. and Roy, A.R. (2002). An application of soft sets in a decision making problem, Computers and Mathematics with Applications 44(8-9): 1077–1083.
[21] [21] Majumdar, P. and Samanta, S.K. (2010). Generalised fuzzy soft sets, Computers and Mathematics with Applications 59(4): 1425–1432.
[22] [22] Meng, D., Zhang, X. and Qin, K. (2011). Soft rough fuzzy sets and soft fuzzy rough sets, Computers and Mathematics with Applications 62(12): 4635–4645.
[23] [23] Molodtsov, D. (1999). Soft set theory—first results, Computers and Mathematics with Applications 37(4–5): 19–31.
[24] [24] Pawlak, Z. (1984). Rough classification, International Journal of Man-Machine Studies 20(5): 469–483.
[25] [25] Pawlak, Z. (1985). Rough sets and decision tables, in A. Skowron (Ed.), Computation Theory. SCT 1984, Lecture Notes in Computer Science, Vol. 208, Springer, Berlin, pp. 187–196.
[26] [26] Peng, X. and Yang, Y. (2017). Algorithms for interval-valued fuzzy soft sets in stochastic multi-criteria decision making based on regret theory and prospect theory with combined weight, Applied Soft Computing 54: 415–430.
[27] [27] Petchimuthu, S., Garg, H., Kamaci, H. and Atagun, A.O. (2020). The mean operators and generalized products of fuzzy soft matrices and their applications in MCGDM, Computational and Applied Mathematics 39(2), Article no. 68.
[28] [28] Qin, H., Ma, X., Herawan, T. and Zain, J.M. (2012). DFIS: A novel data filling approach for an incomplete soft set, International Journal of Applied Mathematics and Computer Science 22(4): 817–828, DOI: 10.2478/v10006-012-0060-3.
[29] [29] Roy, A.R. and Maji, P.K. (2007). A fuzzy soft set theoretic approach to decision making problems, Journal of Computational and Applied Mathematics 203(2): 412–418.
[30] [30] Sun, B., Zhang, M., Wang, T. and Zhang, X. (2020). Diversified multiple attribute group decision-making based on multigranulation soft fuzzy rough set and TODIM method, Computational and Applied Mathematics 39(3), Article no. 186.
[31] [31] Tiwari, V., Jain, P.K. and Tandon, P. (2017). A bijective soft set theoretic approach for concept selection in design process, Journal of Engineering Design 28(2): 100–117.
[32] [32] Tiwari, V., Jain, P.K. and Tandon, P. (2019). An integrated Shannon entropy and TOPSIS for product design concept evaluation based on bijective soft set, Journal of Intelligent Manufacturing 30(4): 1645–1658.
[33] [33] Xu, W., Pan, Y., Chen, W. and Fu, H. (2019). Forecasting corporate failure in the Chinese energy sector: A novel integrated model of deep learning and support vector machine, Energies 12(12), Article no. 2251.
[34] [34] Yang, J. and Yao, Y. (2020). Semantics of soft sets and three-way decision with soft sets, Knowledge-Based Systems 194, Article no. 105538.
[35] [35] Zadeh, L.A. (1965). Fuzzy sets, Information and Control 8(3): 338–353.
[36] [36] Zhang, Z.M. and Zhang, S.H. (2013). A novel approach to multi attribute group decision making based on trapezoidal interval type-2 fuzzy soft sets, Applied Mathematical Modelling 37(7): 4948–4971.
[37] [37] Zou, Y. and Xiao, Z. (2008). Data analysis approaches of soft sets under incomplete information, Knowledge-Based Systems 21(8): 941–945.