Edge-fuzzy graphs constitute an essential modeling paradigm across a broad spectrum of domains ranging from artificial intelligence to computational neuroscience and social network analysis. Under this model, fundamental graph properties such as edge length and graph diameter become stochastic and as such they are consequently expressed in probabilistic terms. Thus, algorithms for fuzzy graph a...

A new method to clustering analysis, which is based on integration of graph theoretical method and fuzzy objective fimction algorithm, is developed. The connectivity mritriv derived from fuzzy limited neighborhood graph and the measurement for similarity and dissimilarity a re utilized to build a new fuzzy objective function that iinifles global data distribution and local spatial information. ...

A systematic procedure for developing the unified signal flow graph model of a fuzzy PI controller is presented in this paper. From this unified model it is possible to determine the complete behavior of the Fuzzy PI controller. As a first step in constructing the signal flow graph the analytical structures oflinear fuzzy PI controller are needed. In view of this by considering triangular/trape...

This paper describes a news summarization system using the Fuzzy Graph based Document Model. News articles are modelled as fuzzy graphs whose nodes are sentences and edges are weighted by the fuzzy similarity measure between the sentences. The similarity between sentences is in between 0 and 1. Centrality of the graph retrieves important sentences. The proposed system produces summaries by Eige...