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This work mainly focuses on different distance concepts in fuzzy graphs. The properties of d distance, distance and gdistance are studied and defined ssdistance in a connected fuzzy graph. A study of gdistance 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.
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