Design of Genetic Algorithm-Based Fuzzy Classification Systems

Fuzzy classification systems play an important role in dealing with uncertainty and vagueness inherent in multidimensionalpattern classification problems. Finding an optimal fuzzy rule set is a milestone in order for fuzzyclassification systems to be built. In this paper, a fuzzy Genetic Algorithm (GA) is developed to generate fuzzyclassification rules with appropriate number of rules in order to maximize the number of correct ly classified patterns .The proposed algorithm is applied to a collection of data contained in 2D images captured by a video camera toidentify the class of moving objects in a traffic scene. The simulation results are compared with other methods in orderto illustrate the efficiency of the proposed method.

کلیدواژه ها:

Fuzzy classification systems ، Machine learning ، Genetic Algorithm