The fuzzy Cmeans algorithm was improved to break through the existing performance limitations.The function of probability consistency was used to determine the original clustering center and the clustering number.For each object an inhibitory factor was added to its opponent to accelerate the convergence.A new validity index which takes a balance between intraclustering and interclustering variation was proposed to act as the aim function.Experiments show that the improved algorithm behaves comparatively higher performance in convergence speed and clustering quality.