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.