Pattern Recognition Letters
An algorithm to compute the supremum of max-min powers and a property of fuzzy graphs
Pattern Recognition Letters
An optimal algorithm to find the degrees of connectedness in an undirected edge-weighted graph
Pattern Recognition Letters
A characterization of fuzzy trees
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy end nodes in fuzzy graphs
Information Sciences: an International Journal
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
Bioinformatics
Is there a need for fuzzy logic?
Information Sciences: an International Journal
Types of arcs in a fuzzy graph
Information Sciences: an International Journal
Computers & Mathematics with Applications
Information Sciences: an International Journal
A characterization of partial blocks in weighted graphs
Information Processing Letters
Intuitionistic fuzzy hypergraphs with applications
Information Sciences: an International Journal
Menger's theorem for fuzzy graphs
Information Sciences: an International Journal
Bipolar fuzzy graphs with applications
Knowledge-Based Systems
Fuzzy graph modeling for text segmentation from land map images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Cycle connectivity in fuzzy graphs
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The fuzzy graph approach is more powerful in cluster analysis than the usual graph - theoretic approach due to its ability to handle the strengths of arcs effectively. The concept of node-strength sequence is introduced and is studied in a complete fuzzy graph. Two new connectivity parameters in fuzzy graphs namely, fuzzy node connectivity (@k) and fuzzy arc connectivity (@k^') are introduced and obtained the fuzzy analogue of Whitney's theorem. Fuzzy node cut, fuzzy arc cut and fuzzy bond are defined. Fuzzy bond is a special type of a fuzzy bridge. It is proved that at least one of the end nodes of a fuzzy bond is a fuzzy cutnode. It is shown that @k=@k^' for a fuzzy tree and it is the minimum of the strengths of its strong arcs. The relationships of the new parameters with already existing vertex and edge connectivity parameters are studied and is shown that the value of all these parameters are equal in a compete fuzzy graph. Also a new clustering technique based on fuzzy arc connectivity is introduced.