Genetic Programming For Fuzzy System Identification
While genetic algorithms are very powerful tools to identify the fuzzy membership functions of a pre-defined rule base, they have their limitation especially when it also comes to identify the input and output variables of a fuzzy system from a given set of data. Genetic programming has been used to identify the input variables, the rule base as well as the involved membership functions of a fuzzy model (Bastian, 2000)
Read more about this topic: Genetic Fuzzy Systems
Famous quotes containing the words genetic, programming, fuzzy and/or system:
“Man is not merely the sum of his masks. Behind the shifting face of personality is a hard nugget of self, a genetic gift.... The self is malleable but elastic, snapping back to its original shape like a rubber band. Mental illness is no myth, as some have claimed. It is a disturbance in our sense of possession of a stable inner self that survives its personae.”
—Camille Paglia (b. 1947)
“If there is a price to pay for the privilege of spending the early years of child rearing in the driver’s seat, it is our reluctance, our inability, to tolerate being demoted to the backseat. Spurred by our success in programming our children during the preschool years, we may find it difficult to forgo in later states the level of control that once afforded us so much satisfaction.”
—Melinda M. Marshall (20th century)
“What do you think of us in fuzzy endeavor, you whose directions are sterling, whose lunge is straight?
Can you make a reason, how can you pardon us who memorize the rules and never score?”
—Gwendolyn Brooks (b. 1917)
“The genius of any slave system is found in the dynamics which isolate slaves from each other, obscure the reality of a common condition, and make united rebellion against the oppressor inconceivable.”
—Andrea Dworkin (b. 1946)