1. Encoding Rules IF Taste is Worse AND Quantity is Sleak THEN Tip is Little IF Taste is Average AND Quantity is Abundant THEN Tip is Average IF Taste is Delicious AND Quantity is Medium THEN Tip is High IF Taste is Delicious AND Quantity is Abundant THEN Tip is High

2. Encoding – Membership functions  (x) 1.0 0.5 -3  R -2  R -1  R 1L1L 2L2L 3L3L 0

3. Objective Function (OF) Objective function is the MSE (mean squared error) on supervisory data of the given Fuzzy System individual

4. Genetic Operators Applied on genetic MF encoding of membership functions Types –Crossover –Mutation –Set similar –Set zero –Set unity

5. Genetic Operators – Mutation (random) parent LL RR mean mutation cell LL RR mean child

6. Genetic Operators - Crossover cutoff  { child 1child 2 parent Bparent A LL RR mean LL RR

7. Neuro Fuzzy Input 1 Input 2 Input Layer Hidden Layer Output Layer Output 1 Rule Implication Defuzzification Rule W 1,1 MF Composition W 1,2 W 1,3