中文说明：资源描述模糊聚类虽然能够对数据聚类挖掘，但是由于网络入侵特征数据维数较多，不同入侵类别间的数据差别较小，不少入侵模式不能被准确分类，基于此，本程序采用结合模糊聚类和广义神经网路回归的聚类算法对入侵数据进行了分类，并通过仿真实验验证了算法可行性。
English Description：
Application backgroundFuzzy clustering, although it can for clustering data mining, but due to the characteristics of the network intrusion data more dimensions, small data difference between different invasion categories, many intrusion model can not be accurately classified. Based on these, the program by combining fuzzy clustering and generalized neural network of clustering algorithm, classification of intrusion data, and through simulation experiments validated the feasibility of the algorithm.