Review and Improvement of Several Optimal Intelligent Pitch Controllers and Estimator of WECS via Artificial Intelligent Approaches - Complex System Modelling and Control Through Intelligent Soft Computations - page 507

6.1 Classi er System

For classi first, genetic algorithm generates an inceptive resident of fuzzy if-then

rules or SCC. Each of them is leaded arbitrary. The perquisite class and the assu-
redly grad of every single fuzzy if-then mandate or SCC are manifest by Ishibuchi
(Hisao et al. 1999 ; Azar 2010b ). In second step it estimates each fuzzy if-then edict
or SCC in the progression residents. Next, genetic algorithm results in new fuzzy
if-then laws or SCC by genetic operation like: crossover, mutation, selection.
In semi

er

nal it restores a part of the progression public with newly generated
fuzzy if then rules or SCC. Finally if a pre-identi ed stopping share isn ' t content,

comeback to second step.

Result in an inceptive resident of fuzzy if-
then rules or SCC

Estimate each fuzzy if-then edict or
SCC in the progression residents.

Result in new fuzzy if-then laws or SCC
by genetic operation like: crossover, mu-
tation, selection.

Restore a part of the progression public
with newly generated fuzzy if then rules
or SCC

a pre-identified
stopping share
isn't content