基于改进遗传算法的计算机网络数据聚类方法

Computer network data clustering method based on improved genetic algorithm

为提高计算机网络数据的聚类效果,提出了一种基于改进遗传算法的计算机网络数据聚类方法。其采用改进遗传算法构建初始种群,利用目标函数提取计算机网络特征,构建计算机网络数据信息流模型聚类计算机网络数据。仿真结果表明,该方法的数据流处理任务完成总时间较短、负载均衡性较稳定、CPU占用率较低。由此证明,该方法数据聚类效果较优。

In order to improve the clustering effect of computer network data,a computer network data clustering method based on improved genetic algorithm is proposed.The improved genetic algorithm is used to construct the initial population,and the objective function is used to extract the characteristics of the computer network,and the computer network data information flow model is constructed to cluster the computer network data.The simulation results show that the proposed method has shorter total time to complete data stream processing tasks,more stable load balancing,and lower CPU utilization.It is proved that the data clustering effect of the proposed method is better.