Research of Improved Fuzzy c-means Algorithm Based on a New Metric Norm

For the question that fuzzy c-means （FCM） clustering algorithm has the disadvantages of being too sensitive to the initial cluster centers and easily trapped in local optima, this paper introduces a new metric norm in FCM and particle swarm optimization （PSO） clustering algorithm, and proposes a parallel optimization algorithm using an improved fuzzy c-means method combined experiment shows that the AF-APSO can avoid local optima, significantly. with particle swarm optimization （AF-APSO）. The and get the best fitness and clustering performance