A fuzzy clustering algorithm of data mining based on IWO

FCM algorithm is sensitive to initial clustering centers and noise data which easily fall into local optimum that cannot reach global optimum. To solve this problem, a fuzzy clustering algorithm of data mining based on IWO is proposed in this paper. We introduce invasive weed optimization with strong robustness and global optimization ability to find the optimal solution as the initial clustering centers for FCM algorithm, and finally obtain the global best optimal solution by using FCM algorithm to initialize the cluster centers, which effectively overcomes the shortcomings of FCM algorithm. Compared with the results of using genetic algorithm, particle swarm optimization algorithm optimal FCM algorithm, the simulation results of this paper´s proposed algorithm is more accurate and better clustering efficiency.