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A Learning Process for Fuzzy Control Rules using GA

A Learning Process for Fuzzy Control Rules using GA. Presented by Alp Sardağ. Goal. Learning fuzzy control rules from examples. Three steps: Generation of fuzzy rules with iteration. Combination of expert rules and the previously generated rules; removing redundant rules.

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A Learning Process for Fuzzy Control Rules using GA

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  1. A Learning Process for Fuzzy Control Rules using GA Presented by Alp Sardağ

  2. Goal • Learning fuzzy control rules from examples. • Three steps: • Generation of fuzzy rules with iteration. • Combination of expert rules and the previously generated rules; removing redundant rules. • Tuning membership functions.

  3. Motivation • Converting the experts know-how into if-then rules is difficult. • Conflicting knowledge. • İnclude inspiration and intuition. • Apply automatic techniques to obtain fuzzy control rules.

  4. Methodology • Based on three stages: • Genetic Generating Process. • Genetic Process for Combining rules and simplifying them. • Genetic Tuning Process.

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