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This work mainly focuses on different distance concepts in fuzzy graphs. The properties of δ- distance,µ -distance and g-distance are studied and defined ss-distance in a connected fuzzy graph. A study of g-distance in a fuzzy tree and its associated maximum spanning tree is carried out.Various types of degrees of a node and its properties in fuzzy graphs are studied. The concept of strong cycle is introduced and studied the properties of fuzzy end nodes and strong cycles in a fuzzy graph. Clustering techniques using distance concepts in fuzzy graphs are discussed and introduced a procedure for finding clusters of order k using distance matrix. Also clustering techniques based on the connectedness concepts in fuzzy graphs are discussed. Fuzzy graph theoretic techniques are applied in fuzzy neural network.
About the Author: Dr.Sameena Kalathodi is Assistant Professor,Mathematics Department,M.E.S Mampad College,University of Calicut.Completed Ph.D from NIT Calicut.Several papers published in international journals.Awarded Women scientist fellowship(2009)by Department of Science and technology,India.Interested Area: Fuzzy Mathematics, Graph Theory,Applied Mathematics.
Title: Distance in Fuzzy Graphs: g-distance, µ -...
Publisher: LAP LAMBERT Academic Publishing
Publication Date: 2012
Binding: Paperback
Condition: Like New
Book Type: book