The traditional fuzzy C-means(FCM) algorithm is an optimization algorithm based on gradient descending, it is sensitive to the initial condition and liable to be trapped in a local optimum. Search space smoothing allows a local search heuristics to escape from a poor, local optimum. In this paper, an improved FCM algorithm based on search space smoothing is proposed. By designing a proper smoot...

Proposed the Algorithm of K-means (CPSOKM) based on Chaos Particle Swarm in order to solve the problem that K-means algorithm sensitive to initial conditions and is easy to influence the clustering effect. On the selection of the initial value problem, algorithm using particle swarm algorithm to balance the random value uncertainty, and then by introducing a chaotic sequence, the particles move...