Bipolar fuzzy soft information applied to hypergraphs

Sarwar, Musavarah; Akram, Muhammad; Shahzadi, Sundas

doi:10.1007/s00500-021-05610-x

Cited by 34 publications

(14 citation statements)

References 36 publications

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“…To describe all real-world competitions, fuzzy competition graphs were introduced by integrating powerful techniques of fuzzy sets and competition graphs Sarwar et al [30] Suggested a powerful novel framework of fuzzy competition hypergraphs to sort out the gaps of above-mentioned techniques Shahzadi et al [32] To handle positive as well as negative degrees, the idea of BF competition hypergraphs, as a generalized form of fuzzy competition hypergraphs was introduced Akram and Nawaz [18] A new mathematical approach FS graphs based on parameters was presented to define uncertainty in several directions Sarwar et al [33] Due to the loss of important information, e.g., given objects satisfying identical characterization, there is a need to depict the data as a hypergraph under bipolar FS information.…”

Section: Motivation and Contributionmentioning

confidence: 99%

Decision-making methods based on fuzzy soft competition hypergraphs

Akram

Shahzadi

Rasool

et al. 2022

Complex Intell. Syst.

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Fuzzy soft set theory is an effective framework that is utilized to determine the uncertainty and plays a major role to identify vague objects in a parametric manner. The existing methods to discuss the competitive relations among objects have some limitations due to the existence of different types of uncertainties in a single mathematical structure. In this research article, we define a novel framework of fuzzy soft hypergraphs that export the qualities of fuzzy soft sets to hypergraphs. The effectiveness of competition methods is enhanced with the novel notion of fuzzy soft competition hypergraphs. We study certain types of fuzzy soft competition hypergraphs to illustrate different relations in a directed fuzzy soft network using the concepts of height, depth, union, and intersection simultaneously. We introduce the notions of fuzzy soft k-competition hypergraphs and fuzzy soft neighborhood hypergraphs. We design certain algorithms to compute the strength of competition in fuzzy soft directed graphs that reduce the calculation complexity of existing fuzzy-based non-parameterized models. We analyze the significance of our proposed theory with a decision-making problem. Finally, we present graphical, numerical, as well as theoretical comparison analysis with existing methods that endorse the applicability and advantages of our proposed approach.

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Section: Motivation and Contributionmentioning

confidence: 99%

Decision-making methods based on fuzzy soft competition hypergraphs

Akram

Shahzadi

Rasool

et al. 2022

Complex Intell. Syst.

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“…Different types of applications of BFGs founded in [6]. The concept of fuzzy soft and bipolar fuzzy soft graphs and their application in wireless Internet founded in [27,28]. Poulik and Ghorai [23] initiated geodesic distance and different types of nodes in BFGs with their applications.…”

Section: Literature Review and Preliminariesmentioning

confidence: 99%

Applications of graph’s complete degree with bipolar fuzzy information

Poulik

Ghorai

2021

Complex Intell. Syst.

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Due to the presence of two opposite directional thinking in relationships between countries and communication systems, the systems may not always be balanced. Therefore, the perfectness between countries relations are highly important. It comes from how much they were connected to each other for communication. In this study, first perfectly regular bipolar fuzzy graph is introduced and examined the regularity of nodes. Then, the relationship between the adjacent nodes and their regularity are visualized as a perfectly edge-regular bipolar fuzzy graphs. The totally accurate communication between all connected nodes is explained by introducing completely open neighborhood degree and completely closed neighborhood degree of nodes and edges in a bipolar fuzzy graph. Some algorithms and flowcharts of the proposed methods are given. Finally, two applications of these cogitation are exhibited in two bipolar fuzzy fields. The first one is in international relationships between some countries during cold-war era and the second one is in decision-making between teachers–students communication system for the improvement of teaching.

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“…(0.9,-0.1) (0.9,-0.1) (0.9,-0.1) (0.82,-0.145) v 14 v 16 (0.2,-0.9) (0.1,-0.9) (0.13,-0.9) (0.13,-0.145) v 15 v 16 (0.9,-0.1) (0.4,-0.5) (0.55,-0.38) (0.33,-0. 19) this paper, we directly extend it to bipolar setting, for…”

Section: Domination In Bipolar Intuitionistic Fuzzy Graphsmentioning

confidence: 99%

“…Shirzadi et al [18] developed a fuzzy programming by bipolar approach. Sarwar et al [19] applied Bipolar fuzzy soft information in hypergraph setting. Muhiuddin and Al-Kadi [20] introduced the notion of bipolar fuzzy implicative ideals of a BCK-algebra and determined several properties.…”

Section: Introductionmentioning

confidence: 99%

Domination of Bipolar Fuzzy Graphs in Various Settings

Gong

Hua

Gao

2021

Int J Comput Intell Syst

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Bipolar fuzzy sets are used to describe the positive and negative of the uncertainty of objects, and the bipolar fuzzy graphs are used to characterize the structural relationship between uncertain concepts in which the vertices and edges are assigned positive and negative membership function values to feature the opposite uncertainty elevation. The dominating set is the control set of vertices in the graph structure and it occupies a critical position in graph analysis. This paper mainly contributes to extending the concept of domination in the fuzzy graph to the bipolar frameworks and obtaining the related expanded concepts of a variety of bipolar fuzzy graphs. Meanwhile, the approaches to obtain the specific dominating sets are presented. Finally, a numeral example on city data in Yunnan Province is presented to explain the computing of domination in bipolar fuzzy graph in the specific application.

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Bipolar fuzzy soft information applied to hypergraphs

Cited by 34 publications

References 36 publications

Decision-making methods based on fuzzy soft competition hypergraphs

Decision-making methods based on fuzzy soft competition hypergraphs

Applications of graph’s complete degree with bipolar fuzzy information

Domination of Bipolar Fuzzy Graphs in Various Settings

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