利用q-rung嗜中性模糊软集TOPSIS聚合算子进行多准则群决策

A. Priya, P. Maragatha Meenakshi, Aiyared Iampan, N. Rajesh, Suganthi Mariyappan
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引用次数: 0

摘要

q-rung中性模糊软集(q-rung NVSS)是对中性模糊软集(NVSS)和模糊软集(VSS)的推广。采用TOPSIS聚合运算(AO)对q-rung NVSS进行了讨论。TOPSIS方法作为VSS的扩展,可以有效地进行多准则群决策。通过一个分数函数,目标是找到基于q阶NVSS的正、负理想解。接近值是通过提出最优方案来确定的。我们提供了实际的例子来支持我们的结论。这将导致提供q的模型的结果。考虑所考虑的模型的有效性和有用性可以通过将它们与已提出的模型进行比较来实现。最近的发现引起了相当多的兴趣和迷恋。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selection of neutral networks using q-rung neutrosophic vague soft set TOPSIS aggregating operator setting multi-criteria group decision making
The q-rung neutrosophic vague soft set (q-rung NVSS) is a generalization of the neutrosophic vague soft set (NVSS) and the vague soft set (VSS). The TOPSIS aggregated operation (AO) was used to discuss the q-rung NVSS. As an extension of VSS, the TOPSIS method effectively makes multi-criteria group decision making (MCGDM). With a score function, the goal is to find a positive and negative ideal solution based on q-rung NVSS. Closeness values are determined by presenting optimal alternatives. We provide practical examples to support our conclusions. This results in the outcome of the models for which q is provided. Considering the validity and usefulness of the models under consideration can be achieved by comparing them with those that have been proposed. Recent discoveries have generated quite a bit of interest and fascination.
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