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A fuzzy-nets system has been developed to create fuzzy rule banks and to control nonlinear systems. The training procedure includes five steps. First, fuzzy regions of input and output spaces are defined based on the boundaries of the system. The second step is to generate fuzzy rules by given data sets which are feedback data from the system. Then, conflicting rules are resolved through bottom-up...
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