Christopher G. Coy

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The accurate modeling of a time series using a Sugeno Fuzzy Inference System (FIS) requires an algorithm that can train the FIS to minimize the error of seen and unseen data points. Many researchers have used genetic algorithms to optimize the parameters of the FIS membership functions with a great deal of success. It is presented here that incorporating(More)
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