Fuzzy incidence graphs can be used as models for nondeterministic interconnection networks having extra node-edgerelationships. For example, ramps in a highway system may be modeled as a fuzzy incidence graph so that unexpectedflow between cities and highways can be effectively studied and controlled. Like node and edge connectivity in graphs,node connectivity and arc connectivity in fuzzy inci...

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...

In this article, we introduce some connectivity concepts in bipolar fuzzy graphs. Analogous to fuzzy cutvertices and fuzzy bridges in fuzzy graphs, bipolar fuzzy cutvertices and bipolar fuzzy bridges are introduced and characterized. We also propose the concepts of gain and loss for paths and pairs of vertices. Connectivity in complete bipolar fuzzy graphs is also discussed.

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 ðjÞ and fuzzy arc connectivity ðj0Þ are introduced and ...

Connectivity analysis methodology is suitable to find representative symptoms of a disease. This methodology describes connections between symptoms in particular way and then chooses the group of symptoms that have the high level of connection, or in other words, have strong interconnections between elements of a group. In this paper we investigate the analogy between connectivity analysis and ...

Fuzzy sets theory constitutes a poweful tool, that can lead to more robustness in problems such as image segmentation and recognition. This robustness results to some extent from the partial recovery of the continuity that is lost during digitization. Here we deal with fuzzy connectivity notions. We show that usual fuzzy connectivity definitions have some drawbacks, and we propose a new definit...

Introduction: Virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. The segmentation of airways from CT images is a critical step for numerous virtual bronchoscopy applications. Materials and Methods: To overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy C-mean (FC-FCM), utilized...

The performance of Data partitioning using machine learning techniques is calculated only with distance measures i.e similarity between the transactions is carried out with the help of distance measurement algorithms such as Euclidian distance measure and cosine distance measure. The distance with connectivity (DWC) model is used to estimate distance between transactions with local consistency ...