Research article

Extending neutrosophic set theory: Cubic bipolar neutrosophic soft sets for decision making

  • Received: 12 August 2024 Revised: 19 September 2024 Accepted: 21 September 2024 Published: 26 September 2024
  • MSC : 03B52, 03E72

  • This research introduced cubic bipolar neutrosophic sets (CBNSs), a novel framework that significantly enhanced the capabilities of bipolar neutrosophic sets (BNSs) in handling uncertainty and vagueness within data analysis. By integrating bipolarity and cubic sets, CBNSs provide a more comprehensive and accurate representation of information. We have defined key operations for CBNSs and thoroughly investigated their structural properties. Additionally, we have introduced cubic bipolar neutrosophic soft sets (CBNSSs) as a flexible parameterization tool for CBNSs. To validate the practical utility of CBNSs, we conducted a case study in decision-making. Our algorithmic approach effectively addressed the challenges posed by uncertainty and vagueness in the decision-making process. The results of our research unequivocally demonstrated the superiority of CBNSs over existing methods in terms of accuracy, flexibility, and applicability. By offering a more nuanced representation of information, CBNSs provide a valuable tool for researchers and practitioners tackling complex decision problems.

    Citation: Khulud Fahad Bin Muhaya, Kholood Mohammad Alsager. Extending neutrosophic set theory: Cubic bipolar neutrosophic soft sets for decision making[J]. AIMS Mathematics, 2024, 9(10): 27739-27769. doi: 10.3934/math.20241347

    Related Papers:

  • This research introduced cubic bipolar neutrosophic sets (CBNSs), a novel framework that significantly enhanced the capabilities of bipolar neutrosophic sets (BNSs) in handling uncertainty and vagueness within data analysis. By integrating bipolarity and cubic sets, CBNSs provide a more comprehensive and accurate representation of information. We have defined key operations for CBNSs and thoroughly investigated their structural properties. Additionally, we have introduced cubic bipolar neutrosophic soft sets (CBNSSs) as a flexible parameterization tool for CBNSs. To validate the practical utility of CBNSs, we conducted a case study in decision-making. Our algorithmic approach effectively addressed the challenges posed by uncertainty and vagueness in the decision-making process. The results of our research unequivocally demonstrated the superiority of CBNSs over existing methods in terms of accuracy, flexibility, and applicability. By offering a more nuanced representation of information, CBNSs provide a valuable tool for researchers and practitioners tackling complex decision problems.



    加载中


    [1] L. A. Zadeh, Fuzzy sets, Inf. Control, 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
    [2] L. A. Zadeh, Similarity relations and fuzzy orderings, Inform. Sciences, 3 (1971), 177–200. https://doi.org/10.1016/S0020-0255(71)80005-1 doi: 10.1016/S0020-0255(71)80005-1
    [3] K. M. Lee, Bipolar-valued fuzzy sets and their operations, In: Proc. Int. Conf. Intell. Technol., Bangkok, Thailandgaiwan, 2000,307–312.
    [4] W. R. Zhang, Bipolar fuzzy sets and relations: A computational framework for cognitive modeling and multiagent decision analysis, In NAFIPS/IFIS/NASA'94. Proceedings of the First International Joint Conference of The North American Fuzzy Information Processing Society Biannual Conference, The Industrial Fuzzy Control and Intellige, 1994,305–309.
    [5] K. M. Lee, K. M. Lee, K. J. Cios, Comparison of interval-valued fuzzy sets, intuitionistic fuzzy sets, and bipolar-valued fuzzy sets, Comput. Inform. Technol. 2001,433–439. https://doi.org/10.1142/9789812810885-0055
    [6] B. Q. Hu, K. F. C. Yiu, A bipolar-valued fuzzy set is an intersected interval-valued fuzzy set, Inform. Sciences, 657 (2024), 119980. https://doi.org/10.1016/j.ins.2023.119980 doi: 10.1016/j.ins.2023.119980
    [7] J. G. Lee, K. Hur, Bipolar fuzzy relations, Mathematics, 7 (2019), 1044. https://doi.org/10.3390/math7111044
    [8] G. Wei, C. Wei, H Gao, Multiple attribute decision making with interval-valued bipolar fuzzy information and their application to emerging technology commercialization evaluation, IEEE Access, 6 (2018), 60930–60955. https://doi.org/10.1109/ACCESS.2018.2875261 doi: 10.1109/ACCESS.2018.2875261
    [9] Y. B. Jun, C. S. Kim, K. O. Yang, Cubic sets, Ann. Fuzzy Math. Inform., 4 (2011), 83–98.
    [10] M. Riaz, S. T. Tehrim, Cubic bipolar fuzzy ordered weighted geometric aggregation operators and their application using internal and external cubic bipolar fuzzy data, Comput. Appl. Math., 38 (2019), 87. https://doi.org/10.1007/s40314-019-0843-3 doi: 10.1007/s40314-019-0843-3
    [11] F. Smarandache, Neutrosophic set—a generalisation of the intuitionistic fuzzy sets, In: 2006 IEEE International Conference on Granular Computing, 2006, 38–42.
    [12] H. Wang, F. Smarandache, Y. Zhang, R. Sunderraman, Single valued neutrosophic sets, Infinite Study, 2010.
    [13] I. Deli, M. Ali, F. marandache, Bipolar neutrosophic sets and their application based on multi-criteria decision making problems, In: 2015 International conference on advanced mechatronic systems (ICAMechS), 2015,249–254. https://doi.org/10.1109/ICAMechS.2015.7287068
    [14] I. Deli, S. Yusuf, F. Smarandache, M. Ali, Interval valued bipolar neutrosophic sets and their application in pattern recognition, In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016. https://doi.org/10.1109/FUZZ-IEEE.2016.7738002
    [15] D. Molodtsov, Soft set theory-first results, Comput. Math. Appl., 37 (1999), 19–31. https://doi.org/10.1016/S0898-1221(99)00056-5 doi: 10.1016/S0898-1221(99)00056-5
    [16] P. K. Maji, Neutrosophic soft set, Ann. Fuzzy Math. Inform., 5 (2013), 157–168.
    [17] M. Ali, L. H. Son, I. Deli, N. D. Tien, Bipolar neutrosophic soft sets and applications in decision making, J. Intell. Fuzzy Syst., 33 (2017), 4077–4087. https://doi.org/10.3233/JIFS-17999 doi: 10.3233/JIFS-17999
    [18] P. Arulpandy, M. T. Pricilla, Bipolar neutrosophic graded soft sets and their topological spaces, Infinite Study, 48 (2022).
    [19] M. Riaz, S. T. Tehrim, Cubic bipolar fuzzy set with application to multi-criteria group decision making using geometric aggregation operators, Soft Comput., 24 (2020), 16111–16133. https://doi.org/10.1007/s00500-020-04927-3 doi: 10.1007/s00500-020-04927-3
    [20] Z. Liu, K. Qin, Z. Pei, Similarity measure and entropy of fuzzy soft sets, The Scientific World J., 1 (2014), 161607. https://doi.org/10.1155/2014/161607 doi: 10.1155/2014/161607
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(103) PDF downloads(8) Cited by(0)

Article outline

Figures and Tables

Tables(12)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog