An improved Fuzzy C-means clustering algorithm

In view of the faults of the traditional fuzzy C-means Clustering algorithm in clustering accuracy and convergence speed, the particle swarm optimization algorithm with cross-operation is used to make up for the deficiency of the FCM (Fuzzy C-means) algorithm, thus an improved fuzzy C-Means Clustering algorithm is formed. Simulation experiments on date sets IRIS and KDD CUP99 show that the MFCM (Modified Fuzzy C-means) algorithm is better than FCM algorithm in clustering accuracy and convergence speed, and its performance is reliable in intrusion detection.