نتایج جستجو برای: fuzzy graph

تعداد نتایج: 286112  

2015
Mini Tom Muraleedharan Shetty Sunitha

In this paper the idea of strong sum distance which is a metric, in a fuzzy graph is introduced. Based on this metric the concepts of eccentricity, radius, diameter, center and self centered fuzzy graphs are studied. Some properties of eccentric nodes, peripheral nodes and central nodes are obtained. A characterisation of self centered complete fuzzy graph is obtained and conditions under which...

2014
Mini Tom

Abstract. In this paper the idea of sum distance which is a metric, in a fuzzy graph is introduced. The concepts of eccentricity, radius, diameter, center and self centered fuzzy graphs are studied using this metric. Some properties of eccentric nodes, peripheral nodes and central nodes are obtained. A characterization of self centered complete fuzzy graph is obtained and conditions under which...

2014
J. S. Sathya S. Vimala

Let be a simple undirected fuzzy graph. A subset S of V is called a dominating set in G if every vertex in V-S is effectively adjacent to at least one vertex in S. A dominating set S of V is said to be a Independent dominating set if no two vertex in S is adjacent. The independent domination number of a fuzzy graph is denoted by (G) which is the smallest cardinality of a independent dominating ...

Journal: :Kybernetika 2000
Ernesto Damiani Letizia Tanca Francesca Arcelli Fontana

A flexible query model is presented for semi-structured information stored in well-formed XML documents, modeled as XML fuzzy graphs by computing estimates of the importance of the information associated to XML elements and attributes. The notion of fuzzy graph closure with threshold is then used to obtain a fuzzy extension of the XML fuzzy graphs' topological structure. Weights associated to c...

In this note by considering a complete lattice L, we define thenotion of an L-Fuzzy hyperrelation on a given non-empty set X. Then wedefine the concepts of (POM)L-Fuzzy graph, hypergraph and subhypergroupand obtain some related results. In particular we construct the categories ofthe above mentioned notions, and give a (full and faithful) functor form thecategory of (POM)L-Fuzzy subhypergroups ...

2013
K. R. Sandeep Narayan M. S. Sunitha

Fuzzy Graphs are having numerous applications in problems like Network analysis, Clustering, Pattern Recognition and Neural Networks. The analysis of properties of fuzzy graphs has facilitated the study of many complicated networks like Internet. In this paper we study the structures of complement of many important fuzzy graphs such as Fuzzy cycles, Blocks etc. The complement of fuzzy graphs wi...

2001
Philippe Mulhem Wee Kheng Leow Yoong Keok Lee

Conceptual graphs are very useful for representing structured knowledge. However, existing formulations of fuzzy conceptual graphs are not suitable for matching images of natural scenes. This paper presents a new variation of fuzzy conceptual graphs that is more suited to image matching. This variant differentiates between a model graph that describes a known scene and an image graph which desc...

2014
Leonid Samoilovich Bershtein Stanislav Leonidovich Belyakov Alexander Vitalievich Bozhenyuk Igor Naymovich Rozenberg

In this paper the routing problem in a transport network with fuzzy parameters changing in time is considered. In this connection, the concept of fuzzy temporal graph is introduced. Which one is a generalization of a fuzzy graph on the one hand, and a temporal graph on the other hand. The incidence of graph vertices is changed in the discrete time in fuzzy temporal graph. Fuzzy temporal graph i...

1997
Masao Mori Yasuo Kawahara

This paper presents fuzzy graph rewriting systems with fuzzy relational calculus. In this paper fuzzy graph means crisp set of vetices and fuzzy set of edges. We provide $\mathrm{f}\mathrm{u}\mathrm{z},7,\mathrm{y}$ relational calculus witll Heyting algebra. Formalizing rewriting system of fuzzy graphs it is important to $\mathrm{c}\cdot 1_{1\mathrm{t})\mathrm{t}}.\mathrm{q}\mathrm{C}1$ how to ...

2013
Arindam Dey Anita Pal Sunil Mathew

Let G= (V,E,σ,μ) be a simple connected undirected fuzzy graph. In this paper, we use a fuzzy graph model to represent a traffic network of a city and discuss a method to find the different type of accidental zones in a traffic flows. Depending on the possibility of accident, this paper classifies accidental zone of a traffic flow into three type’s namely α-strong, β-strong and δ-strong accident...

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