多值 Neutrosophic 幂分 Hamy 均值算子及其在多属性群决策中的应用。
Multivalued neutrosophic power partitioned Hamy mean operators and their application in MAGDM.
机构信息
School of Economics and Management, Shandong Agricultural University, Taian, China.
School of Business Administration, Shandong Women's University, Jinan, China.
出版信息
PLoS One. 2023 Feb 15;18(2):e0281734. doi: 10.1371/journal.pone.0281734. eCollection 2023.
The novel multivalued neutrosophic aggregation operators are proposed in this paper to handle the complicated decision-making situations with correlation between specific information and partitioned parameters at the same time, which are based on weighted power partitioned Hamy mean (WMNPPHAM) operators for multivalued neutrosophic sets (MNS) proposed by combining the Power Average and Hamy operators. Firstly, the power partitioned Hamy mean (PPHAM) is capable of capture the correlation between aggregation parameters and the relationship among attributes dividing several parts, where the attributes are dependent definitely within the interchangeable fragment, other attributes in divergent sections are irrelevant. Secondly, because MNS can effectively represent imprecise, insufficient, and uncertain information, we proposed the multivalued neutrosophic PMHAM (WMNPHAM) operator for MNS and its partitioned variant (WMNPPHAM) with the characteristics and examples. Finally, this multiple attribute group decision making (MAGDM) technique is proven to be feasible by comparing with the existing methods to confirm this method's usefulness and validity.
本文提出了新的多值 neutrosophic 聚合算子，以处理具有特定信息和分区参数之间相关性的复杂决策情况，这些算子基于加权幂分 Hamy 均值（WMNPPHAM）算子，用于多值 neutrosophic 集（MNS），由 Power Average 和 Hamy 算子结合提出。首先，幂分 Hamy 均值（PPHAM）能够捕捉聚合参数之间的相关性以及划分成几部分的属性之间的关系，其中属性在可互换的片段内是确定依赖的，其他在发散部分的属性是不相关的。其次，由于 MNS 能够有效地表示不精确、不足和不确定的信息，我们提出了多值 neutrosophic PMHAM（WMNPHAM）算子及其分区变体（WMNPPHAM），并给出了其特点和示例。最后，通过与现有方法进行比较，证明了这种多属性群决策（MAGDM）技术的可行性，以确定该方法的有用性和有效性。
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