Advanced bounds for eigenvalues in spectral fuzzy graph theory

This paper introduces advanced eigenvalue bounds for Spectral Fuzzy Graphs (SFGs), a subclass of fuzzy graphs with symmetric adjacency matrices enhancing the precision of spectral graph analysis. Leveraging the Rayleigh quotient and the Perron-Frobenius theorem, we establish novel upper and lower bounds for the largest and smallest eigenvalues of fuzzy adjacency matrices. Specific results include eigenvalue bounds for complete and bipartite fuzzy graphs, as well as the demonstration of eigenvalue stability under graph perturbations and unions. A numerical example based on a protein interaction network illustrates the practical applicability of the proposed methods, demonstrating improved accuracy in analyzing network resilience and connectivity.

کلیدواژه ها:

Fuzzy graph ، Adjacency eigenvalue ، Laplacian eigenvalue ، spectral radius ، Energy bounds