Correlation measures of Pythagorean hesitant fuzzy set

被引:0
|
作者
Liu W.-F. [1 ]
He X. [1 ]
Chang J. [1 ]
机构
[1] College of Science, Zhengzhou University of Aeronautics, Zhengzhou
来源
Kongzhi yu Juece/Control and Decision | 2019年 / 34卷 / 05期
关键词
Correlation coefficient; Correlation measure; Decision making; Hesitant fuzzy set; Pythagorean fuzzy set; Pythagorean hesitant fuzzy set;
D O I
10.13195/j.kzyjc.2017.1560
中图分类号
学科分类号
摘要
Pythagorean hesitant fuzzy set, which can not only describe the fuzzy phenomenon that the sum of membership degree and nonmembership degree may be bigger than 1 but their square sum is equal to or less than 1, but also express hesitations in membership degree and nonmembership degree, can be considered as a powerful tool for expressing uncertain information in the process of decision making. Considering that correlation measures play important role in statistics and management science, in this paper, correlation measures of the Pythagorean hesitant fuzzy set is studied. On the basis of the definition of the informational energy of the Pythagorean hesitant fuzzy set, the correlation coefficients between Pythagorean hesitant fuzzy sets are defined, and their natures are discussed. Then, the weights of attributes are often taken into account, and the concept of the weighted correlation coefficient between Pythagorean hesitant fuzzy sets is also introduced, and the natures are studied. Finally, through the weighted correlation coefficients between each alternative and the positive ideal alternative, the ranking order of all alternatives can be determined and the best alternative can be identified. An example is given to illustrate the feasibility and applicability of the proposed method. © 2019, Editorial Office of Control and Decision. All right reserved.
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页码:1018 / 1024
页数:6
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共 29 条
  • [1] Zadeh L.A., Fuzzy sets, Information and Control, 8, 3, pp. 338-353, (1965)
  • [2] Atanassov K., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, 1, pp. 87-96, (1986)
  • [3] Atannasov K., Intuitionistic Fuzzy Sets: Theory and Applications, pp. 1-138, (1999)
  • [4] Xu Z.S., Intuitionistic fuzzy aggregation operators, IEEE Trans on Fuzzy Systems, 15, 6, pp. 1179-1187, (2007)
  • [5] Xu Z.S., Yager R.R., Some geometric aggregation operators based on intuitionistic fuzzy sets, Int J of General Systems, 35, 4, pp. 417-433, (2006)
  • [6] Gerstenkorn T., Manko J., Correlation of intuitionistic fuzzy sets, Fuzzy Sets and Systems, 44, 1, pp. 39-43, (1991)
  • [7] Zeng W.Y., Li H.X., Correlation coefficient of intuitionistic fuzzy sets, Int J of Industrial Engineering, 3, 5, pp. 33-40, (2007)
  • [8] Xu Z.S., Chen J., Wu J., Clustering algorithm for intuitionistic fuzzy sets, Information Sciences, 178, 19, pp. 3775-3790, (2008)
  • [9] Xu Z.S., Choquet integrals of weighted intuitionistic fuzzy information, Information Sciences, 180, 5, pp. 726-736, (2010)
  • [10] Zadeh L.A., The concept of a linguistic variable and its application to approximate reasoning-I, Information and Control, 8, 3, pp. 199-249, (1975)