Description: Fuzzy knowledge-based system identification and modeling process is composed of two parts: variable identification and parameter identification. In variable identification, the significant variables of the system are identified among the set of possible variables. In parameter identification, the parameters of the knowledge-based system that describe the relationship between input and the output variables are identified. Parameter identification method consist of two steps: 1-find fuzzy clusters to establish the number of fuzzy rules 2-optimize the rule consequents. This code perform a fuzzy clustering using subtractive clustering
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cluster_sel.m
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