In this paper we introduce the notion of intuitionistic fuzzy f morphism on intutionistic fuzzy graphs and regular intutionistic fuzzy graph. We study the action of intuitionistic fuzzy f morphism on intuitionistic fuzzy strong regular graphs. We derive some simple but elegent results on weak and coweak isomophisms. Mathematics Subject Classification: 03E72, 03F55

Fuzzy-Attribute Graph (FAG) was proposed to handle fuzziness in the pattern primitives in structural pattern recognition. FAG has the advantage that we can combine several possible definitions into a single template, and hence only one matching is required instead of one for each definition. Also, each vertex or edge of the graph can contain fuzzy attributes to model real-life situations. Howev...

Fuzzy-Attribute Graph (FAG) was proposed to handle fuzziness in the pattern primitives in structural pattern recogni~~on [l]. FAG has the advantage that we can combine several possible definition into a single template, and hence only one matching is required instead of one for each definition. Also, each vertex or edge of the graph can contain fuzzy attributes to model real-life situation. How...

Graph transformation, a branch of theoretical computer science, is about the definition of graph languages by grammars, and the study of computations on graphs by rewrite rules. In this paper, we sketch a software engineering problem – the refactoring of object-oriented software – and indicate how graph grammars and graph rewrite rules can be extended for specifying and implementing refactoring...

We show how a fuzzy answer set program can be compiled to an equivalent fuzzy propositional theory whose models correspond to the answer sets of the program. This creates a basis for constructing fuzzy answer set solvers, such as solvers based on fuzzy SAT-solvers or on linear programming.

Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding br...