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On m-polar fuzzy graph structures

机译:关于m极模糊图结构

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摘要

Sometimes information in a network model is based on multi-agent, multi-attribute, multi-object, multi-polar information or uncertainty rather than a single bit. An m-polar fuzzy model is useful for such network models which gives more and more precision, flexibility, and comparability to the system as compared to the classical, fuzzy and bipolar fuzzy models. In this research article, we introduce the notion of m-polar fuzzy graph structure and present various operations, including Cartesian product, strong product, cross product, lexicographic product, composition, union and join of m-polar fuzzy graph structures. We illustrate these operations by several examples. We also investigate some of their related properties.
机译:有时,网络模型中的信息基于多主体,多属性,多对象,多极信息或不确定性,而不是单个位。 m极模糊模型可用于此类网络模型,与经典,模糊和双极模糊模型相比,该模型为系统提供了越来越多的精度,灵活性和可比性。在本文中,我们介绍了m极模糊图结构的概念,并介绍了各种操作,包括笛卡尔乘积,强积,叉积,词典产品,组成,m极模糊图结构的并集和联接。我们通过几个示例来说明这些操作。我们还研究了它们的一些相关属性。

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