Optimization of Multiple Input Single Output Fuzzy Membership Functions Using Clonal Selection Algorithm

A clonal selection algorithm (CLONALG) inspires from Clonal Selection Principle used to explain the basic features of an adaptive immune response to an antigenic Stimulus. In this study, a new method is proposed for optimization of the Multiple Input Single Output (MISO) fuzzy membership functions using CLONALG. The most appropriate placement of membership functions with respect to fuzzy variables can be determined using our method for a fuzzy system whose rules table and shape of membership functions were given previously. Also, how the membership functions compute as a parameter optimization problem using CLONALG is descried for MISO fuzzy system on an illustrative example.