Inference and Reformation in Flow Graphs Using Granular Computing

Flow graph (FG) is a new mathematical model which can be used for representing, analyzing, and discovering knowledge in databases. Due to its well-structured characteristics of network, FG is naturally consistent with granular computing (GrC). Meanwhile, GrC provides us with both structured thinking at the philosophical level and structured problem solving at the practical level. In this paper, the relationship between FG and GrC will be discussed from three aspects under GrC at first, and then inference and reformation in FG can be easily implemented in virtue of decomposition and composition of granules, respectively. As a result of inference and reformation, the reformed FG is a reduction of the original one.

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