Multiple-Attribute Decision-Making Method Based on Correlation Coefficient of Probabilistic Dual Hesitant Fuzzy Information with Unknown Weights of Attribute

被引：0
|
作者：
Song J. [1 ,2 ]
Ni Z. [1 ,2 ]
Wu W. [1 ,2 ]
Jin F. [3 ]
Li P. [1 ,2 ,4 ]
机构：
[1] School of Management, Hefei University of Technology, Hefei
[2] Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei University of Technology, Hefei
[3] School of Business, Anhui University, Hefei
[4] College of Information Engineering, Fuyang Normal University, Fuyang
来源：
Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence | 2022年 / 35卷 / 04期
基金：
中国国家自然科学基金; 安徽省自然科学基金;
关键词：
Attribute Weight; Correlation Coefficient; Multiple-Attribute Decision-Making; Probabilistic Dual Hesitant Fuzzy Set;
D O I：
10.16451/j.cnki.issn1003-6059.202204002
中图分类号：
学科分类号：
摘要：
The probabilistic dual hesitant fuzzy set contains membership degree, non-membership degree and their corresponding probability information. It is an important tool to describe uncertain decision-making information. To solve the probabilistic dual hesitant fuzzy multiple-attribute decision-making problem with unknown attribute weight information, a multiple-attribute decision-making method is proposed based on the correlation coefficient of probabilistic dual hesitant fuzzy information. Firstly, the objective attribute weight is calculated by probabilistic dual hesitant fuzzy information entropy and combined with the subjective attribute weight given by decision-maker to obtain the comprehensive weight of attribute. Secondly, a correlation coefficient and a weighted correlation coefficient are proposed to measure the correlation level between decision-making information, and the excellent properties of the proposed correlation coefficients are analyzed. Finally, a multi-attribute decision-making method based on the correlation coefficient of probabilistic dual hesitant fuzzy information is designed and applied to the selection experiment of haze control strategies. Experimental results show that the proposed method produces good robustness and effectiveness. © 2022, Science Press. All right reserved.
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页码：306 / 322
页数：16
相关论文
共 41 条
  • [21] LIN M W, HUANG C, CHEN R Q, Et al., Directional Correlation Coefficient Measures for Pythagorean Fuzzy Sets: Their Applications to Medical Diagnosis and Cluster Analysis, Complex & Inte-lligent Systems, 7, 2, pp. 1025-1043, (2021)
  • [22] BAKIOGLU G, ATAHAN A O., AHP Integrated TOPSIS and VIKOR Methods with Pythagorean Fuzzy Sets to Prioritize Risks in Self-Driving Vehicles, Applied Soft Computing, (2021)
  • [23] TORRA V., Hesitant Fuzzy Sets, International Journal of Intelligent Systems, 25, 6, pp. 529-539, (2010)
  • [24] ZHU B, XU Z S, XIA M M., Dual Hesitant Fuzzy Sets, Journal of Applied Mathematics, (2012)
  • [25] ZHU B., Decision Method for Research and Application Based on Preference Relation, (2014)
  • [26] KRISHANKUMAR R, RAVICHANDRAN K S, KAR S, Et al., Double-Hierarchy Hesitant Fuzzy Linguistic Term Set-Based Decision Framework for Multi-attribute Group Decision-Making, Soft Computing, 25, pp. 2665-2685, (2021)
  • [27] ZHENG Y F, XU J, CHEN H Z., TOPSIS-Based Entropy Measure for Intuitionistic Trapezoidal Fuzzy Sets and Application to Multi-attribute Decision Making, Mathematical Biosciences and Engineering, 17, 5, pp. 5604-5617, (2020)
  • [28] WANG X K, WANG J Q, ZHANG H Y., Distance-Based Multicriteria Group Decision-Making Approach with Probabilistic Linguistic Term Sets, Expert Systems, 36, 2, (2019)
  • [29] XIANG N, DOU Y J, JIANG J, Et al., Weapon Selection Decision-Making Based on Expert Trust Network under Incomplete Information, Systems Engineering-Theory & Practice, 40, 3, pp. 759-770, (2021)
  • [30] SONG C Y, XU Z S, ZHAO H., New Correlation Coefficients Between Probabilistic Hesitant Fuzzy Sets and Their Applications in Cluster Analysis, International Journal of Fuzzy Systems, 21, 2, pp. 355-368, (2019)
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