Leila Montazeri - Faculty of Electrical and Computer Engineering, Noushirvani Institute of Technology , Babol, Iran.
Reza Ghaderi - Faculty of Electrical and Computer Engineering, Noushirvani Institute of Technology , Babol, Iran.
Ataollah Ebrahimzadeh - Faculty of Electrical and Computer Engineering, Noushirvani Institute of Technology , Babol, Iran

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.

Fuzzy classification systems; Machine learning; Genetic Algorithm