Hypergraph and network flow-based quality function deployment

Abonyi, János; Czvetkó, Tímea

doi:10.1016/j.heliyon.2022.e12263

Cited by 4 publications

(2 citation statements)

References 60 publications

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“…In addition, the book also sheds light on real-world applications of these hypergraphs, making it a valuable resource for students and researchers in the field of mathematics, as well as computer and social scientists [17]. There is also some research about fuzzy (hyper) graphs and their applications in complex hypernetworks, such as the implementation of single-valued neutrosophic soft hypergraphs on the human nervous system [18], decision-making methods based on fuzzy soft competition hypergraphs [19], hypergraph and network flow-based quality function deployment [20], global domination in fuzzy graphs using strong arcs [21], fuzzy hypergraph modeling, analysis and prediction of crimes [22], single-valued neutrosophic directed (hyper) graphs and applications in networks [23], achievable single-valued neutrosophic graphs in wireless sensor networks [24], fuzzy hypergraph network for recommending top-k profitable stocks [25], an algorithm to compute the strength of competing interactions in the bearing sea based on Pythagorean fuzzy hypergraphs [26] and centrality measures in fuzzy social networks [27]. Recently, Smarandache extended hypergraphs to a new concept as nsuperhypergraph and Plithogenic n-superhypergraph which have several properties and are connected with the real-world [28].…”

Section: Introductionmentioning

confidence: 99%

Decision Making Based on Valued Fuzzy Superhypergraphs

Hamidi,

Smarandache,

Taghinezhad

2024

CMES

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This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept. We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole to the whole group of objects at the same time. We have investigated the properties of fuzzy (quasi) superhypergraphs based on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valued fuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based on the permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi) superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introduced in this study and it is applied in designing the real problem in the real world. Finally, the problem of business superhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.

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Section: Introductionmentioning

confidence: 99%

Decision Making Based on Valued Fuzzy Superhypergraphs

Hamidi,

Smarandache,

Taghinezhad

2024

CMES

View full text Add to dashboard Cite

show abstract

“…Additional emerging graph-based modeling and analysis method relays on hypergraphs, which is a generalization of a graph, where an edge (also known as a hyperedge) can connect more than two vertices. Hypergraph-based representation and analysis can be applied to identify the indirect interactions in a complex system or data structure [ 16 ] or can support the human-centric approach as described in connection with the so-called Intelligent collaborative manufacturing space [ 17 ] as well. It can be concluded, that graph or hypergraph-based semantic networks as ontologies or knowledge graphs has a high potential to facilitate data integration and contextualization in Industry 4.0 and 5.0 environments.…”

Section: Introductionmentioning

confidence: 99%