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
Is there a need for fuzzy logic?
Information Sciences: an International Journal
Types of arcs in a fuzzy graph
Information Sciences: an International Journal
Node connectivity and arc connectivity of a fuzzy graph
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy preference based rough sets
Information Sciences: an International Journal
Information Sciences: an International Journal
Soft fuzzy rough sets for robust feature evaluation and selection
Information Sciences: an International Journal
On averaging operators for Atanassov's intuitionistic fuzzy sets
Information Sciences: an International Journal
Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures
Information Sciences: an International Journal
On the accessibility/controllability of fuzzy control systems
Information Sciences: an International Journal
Grey-prediction self-organizing fuzzy controller for robotic motion control
Information Sciences: an International Journal
Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets
Information Sciences: an International Journal
Hi-index | 0.07 |
The concept of the strongest path plays a crucial role in fuzzy graph theory. In classical graph theory, all paths in a graph are strongest, with a strength value of one. In this article, we introduce Menger's theorem for fuzzy graphs and discuss the concepts of strength-reducing sets and t-connected fuzzy graphs. We also characterize t-connected and t-arc connected fuzzy graphs.