DNA genetic algorithms for design of fuzzy systems

A new DNA genetic algorithm (DNA-GA) based on the mechanism of biological DNA and genetic information is proposed. The genetic operators of the DNA-GA are discussed. The DNA encoding method is suitable for the representation of complex knowledge. The DNA-GA is employed to design effective generalized fuzzy systems (GFS) for the modeling and control applications. GFS employ arbitrary fuzzy rules, e(-|/spl alpha//sub 1/x/sub 1/+/spl alpha//sub 2/|)-type input fuzzy sets containing almost arbitrary continuous input fuzzy sets, arbitrary singleton output fuzzy sets, arbitrary fuzzy logic AND, and the generalized defuzzifier containing the widely-used centroid defuzzifier as a special case. The DNA-GA is used to select input variables and to tune the design parameters and membership functions of GFS. As such, the fuzzy rule sets of GFS can be obtained. The work in this paper provides a useful way for the design of fuzzy controllers and fuzzy models.