Evolutionary Strategies for Fuzzy Models: Local vs Global Construction
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This paper presents a framework for studying the effectiveness of evolutionary strategies for generating fuzzy rule bases from training data. The fitness measure needed for selection is obtained by a comparison of the training data with the function approximation defined by a fuzzy rule base. The properties of employing both global and local fitness measures are examined. Rule base completion is obtained by incorporating a global evaluation of the smoothness of the transitions between local regions into the selection process.
& Spiegel, D.
(1999). Evolutionary Strategies for Fuzzy Models: Local vs Global Construction. 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS, 203-207.