the data flow in dynamic environment prone to concept drift phenomenon, gradually along with the data, implicit knowledge in a certain extent can appear in the data change, the current data classification method to dynamic update, not suitable for the classification of the data in dynamic environment.For this, put forward a new data classification method based on particle swarm optimization algorithm, through the method of K - means classifying data in dynamic environment, this paper introduces the particle swarm optimization algorithm, all individuals will be considered a d d no volume of particles in search space, in the search space flight at a certain speed, the speed can be through its own dynamic adjustment and adjacent particles flying experience, through some rules to update the local optimal value of new particles, using the optimized particle swarm algorithm for data classification.The experimental results show that the proposed method classification performance, high accuracy in real time.