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- Title
Fuzzy Anti-Magic Labeling on Comb and Twing Graphs.
- Authors
Selvarasu, Suruthi; Murugan, Shanmuga Sundari
- Abstract
Fuzzy labeling in graph theory is important because it enhances the modelling of uncertainties, gives relationships a granular representation, makes network models more robust, enables clustering and community detection, contributes to decision making, enables machine learning and data mining, and has applications in different fields where complex structures need to be expressed with degrees of membership or uncertainty. In this paper, we proved that the twing and comb graphs admit fuzzy labeling by providing an algorithm. Also, we show that the twing and comb graphs reveal vertex and edge anti-magic labeling. Fuzzy end vertex, fuzzy bridge, degree, strong degree, and strong edge are mostly related to connectivity, so they may be applied to networking. Because of that, we have derived some properties related to the fuzzy end vertex, fuzzy bridge, degree, strong degree, and strong edge have been discussed.
- Subjects
GRAPH labelings; FUZZY graphs; FUZZY decision making; DATA mining; MACHINE learning
- Publication
Mathematical Modelling of Engineering Problems, 2024, Vol 11, Issue 2, p500
- ISSN
2369-0739
- Publication type
Article
- DOI
10.18280/mmep.110222