A Clustering Algorithm for Triangular Fuzzy Normal Random Variables

Li, Ye; Chen, Yiyan; Li, Qun

doi:10.1007/s40815-020-00933-7

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…Thereafter, Liu et al extended the density operator to the form of triangular intuitionistic fuzzy numbers [29], and Lin et al proposed the intuitionistic fuzzy number density operator [30]. Zhang et al developed the two-dimensional density operator and applied it to the group evaluation [31]. Clustering is a key step in the application of density operator.…”

Section: Introductionmentioning

confidence: 99%

Method for Triangular Fuzzy Multiple Attribute Decision Making Based on Two-Dimensional Density Operator Method

Lin,

Li,

Liu

et al. 2024

J. of Syst. Eng. Electron.

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Aiming at the triangular fuzzy (TF) multi-attribute decision making (MADM) problem with a preference for the distribution density of attribute (DDA), a decision making method with TF number two-dimensional density (TFTD) operator is proposed based on the density operator theory for the decision maker (DM). Firstly, a simple TF vector clustering method is proposed, which considers the feature of TF number and the geometric distance of vectors. Secondly, the least deviation sum of squares method is used in the program model to obtain the density weight vector. Then, two TFTD operators are defined, and the MADM method based on the TFTD operator is proposed. Finally, a numerical example is given to illustrate the superiority of this method, which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

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Section: Introductionmentioning

confidence: 99%