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首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >Ranking methodology of induced Pythagorean trapezoidal fuzzy aggregation operators based on Einstein operations in group decision making
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Ranking methodology of induced Pythagorean trapezoidal fuzzy aggregation operators based on Einstein operations in group decision making

机译:基于爱因斯坦作用的诱导毕达哥仑梯形模糊聚集运算符的排名方法

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摘要

The Pythagorean fuzzy number is a new tool for uncertainty and vagueness. It is a generalization of fuzzy numbers and intuitionistic fuzzy numbers. In this paper, we define some Einstein operations on Pythagorean trapezoidal fuzzy set and develop two averaging aggregation operators, which is an induced Pythagorean trapezoidal fuzzy Einstein ordered weighted averaging operator and an induced Pythagorean trapezoidal fuzzy Einstein hybrid averaging (I-PTFEHA) operator. We presented some new methods to deal with the multi-attribute group decision-making problems under the Pythagorean trapezoidal fuzzy environment. Finally, we used some practical examples to illustrate the validity and feasibility of the proposed methods by comparing with existing method. It shows that the proposed I-PTFEHA operator is much better and reliable than the existing one.
机译:毕达哥兰模糊数是一种用于不确定性和模糊性的新工具。 它是模糊数和直觉模糊数的概括。 在本文中,我们在毕达哥兰梯形模糊集上定义了一些爱因斯坦操作,并开发了两个平均聚集运算符,该钙血三角梯形模糊Einstein有序加权平均操作员和诱导的毕达哥兰梯形模糊爱因斯坦·平均(I-PTFEHA)操作员。 我们提出了一些新的方法来处理毕达哥拉斯梯形模糊环境下的多属性组决策问题。 最后,我们使用一些实际的例子来说明通过与现有方法进行比较来说明所提出的方法的有效性和可行性。 它表明,所提出的I-PTFEHA算子比现有的I-PTFEHA操作员要更好。

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