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Multiple attribute decision making method based on normal neutrosophic generalized weighted power averaging operator

机译:基于常规中智广义加权平均功率算子的多属性决策方法

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摘要

Normal neutrosophic numbers (NNNs) are an important tool to describe the decision making problems, and they are more appropriate to express the incompleteness, indeterminacy and inconsistency of the evaluation information. In this paper, we firstly introduce the definition, the properties, the score function, the accuracy function, and the operational laws of the NNNs. Then, some operators are proposed, such as the normal neutrosophic power averaging operator, the normal neutrosophic weighted power averaging operator, the normal neutrosophic power geometric operator, the normal neutrosophic weighted power geometric operator, the normal neutrosophic generalized power averaging operator, the normal neutrosophic generalized weighted power averaging (NNGWPA) operator. Furthermore, some properties of them are discussed. Thirdly, we propose a multiple attribute decision making method based on the NNGWPA operator. Finally, we use an illustrative example to demonstrate the practicality and effectiveness of the proposed method.
机译:正常中性神经元(NNN)是描述决策问题的重要工具,它们更适合表达评估信息的不完全性,不确定性和不一致性。在本文中,我们首先介绍了神经网络的定义,性质,得分函数,准确性函数以及运算规律。然后,提出了一些算子,如正常中智功率平均算子,正常中智加权功率平均算子,正常中智功率几何算子,正常中智加权功率几何算子,正常中智广义功率平均算子,正常中智广义加权平均功率(NNGWPA)运算符。此外,讨论了它们的一些特性。第三,提出了一种基于NNGWPA算子的多属性决策方法。最后,我们用一个说明性的例子来证明所提方法的实用性和有效性。

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